UNIVERSITY of CALIFORNIA RIVERSIDE Black Hole Feedback

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UNIVERSITY OF CALIFORNIA RIVERSIDE

Black Hole Feedback in Dwarf Galaxy Evolution

A Dissertation submitted in partial satisfaction of the requirements for the degree of

Doctor of Philosophy

Physics

Christina Manzano King

September 2020

Dissertation Committee:

Prof. Gabriela Canalizo, Chairperson Prof. Frederick Hamann Prof. Brian Siana Copyright by Christina Manzano King 2020 The Dissertation of Christina Manzano King is approved:

Committee Chairperson

University of California, Riverside Acknowledgments

I would like to express my sincere gratitude to my advisor Prof. Canalizo for her continued patience and hard work mentoring me. I would also like to thank the rest of my thesis committee for their insightful comments, my group for their continued help throughout this project, and my friends in POWUR who held me up along the way. To those defending the sacred: Kū Kia‘i Mauna!

iv I dedicate my work to Jose Lucero Manzano and Valentina Tuazon Manzano, who dreamt that their granddaughter would earn the family’s first doctorate degree, and

to Ruena Manzano, who supports me in all I do.

v ABSTRACT OF THE DISSERTATION

Black Hole Feedback in Dwarf Galaxy Evolution

Christina Manzano King

Doctor of Philosophy, Graduate Program in Physics University of California, Riverside, September 2020 Prof. Gabriela Canalizo, Chairperson

In a scenario where all galaxies form and evolve with supermassive black holes in their centers, it is thought that these central black holes play a vital role in limiting the growth of massive galaxies. In order to extend our understanding of black hole influence on galaxy evolution into the low mass regime, we collected spatially resolved spectra of

10 50 nearby (z < 0.05) dwarf (M⋆ < 10 M⊙) galaxies, selected from SDSS DR7 and DR 8 followed-up with Keck/LRIS spectroscopy. We study the potential effects of active galactic nuclei (AGN) on galaxy-wide gas kinematics and integrated stellar properties by comparing measurements obtained from 29 galaxies containing AGN, and 21 control galaxies with no optical or infrared signs of AGN. We present the first direct measurements of AGN-driven gas outflows in the low mass regime. We also find a strong association betweenAGN and disturbed ionized gas kinematics and signs of star formation suppression. Our results provide evidence that AGN can have significant influence on large scale gas motions in their host galaxies and their global stellar populations. AGN feedback appears to be an

vi important, and perhaps dominant, mechanism that regulates dwarf galaxy evolution, and should be included in realistic galaxy formation models in the low-mass regime.

vii Contents

List of Figures 3

List of Tables 16

1 Introduction 1 Introduction ...... 1 1.1 Small Scale Problems ...... 2 1.2 An Overview of Baryonic Feedback ...... 5 1.2.1 Stellar feedback ...... 5 1.2.2 AGN feedback ...... 5 1.3 This Work ...... 7

2 Outflows 8 2.1 Introduction ...... 9 2.2 Data ...... 12 2.2.1 Sample Selection ...... 12 2.2.2 Observations and Data Reduction ...... 14 2.3 Analysis ...... 17 2.3.1 Fitting the Stellar Continuum ...... 18 2.3.2 Fitting Emission Lines ...... 19 2.3.3 Detecting Outflows ...... 21 2.3.4 Outflow Velocity ...... 22 2.3.5 Decomposed Flux Ratios ...... 23 2.4 Results ...... 24 2.4.1 Classifying Outflows ...... 24 2.4.2 Integrated Properties of Outflows ...... 26 2.4.3 Spatially Resolved Properties of Outflows ...... 29 2.5 Discussion ...... 31 2.5.1 Ionization by Star Formation vs. AGN ...... 31 2.5.2 Outflow Line Profiles ...... 32 2.5.3 Gas Velocity ...... 36 2.5.4 Feedback ...... 37

1 2.6 Summary ...... 40

3 Gas Kinematics 45 3.1 Introduction ...... 46 3.2 Data ...... 48 3.3 Analysis ...... 55 3.3.1 Spatially Resolved Spectra ...... 55 3.3.2 Emission Line Fluxes ...... 57 3.3.3 Multi-Component Velocity Measurements ...... 57 3.3.4 Circular Velocity Curves ...... 58 3.4 Results ...... 60 3.4.1 Comparison with NFW ...... 60 3.4.2 Peculiar Gas ...... 66 3.4.3 Star Formation Suppression ...... 70 3.4.4 Environment ...... 73 3.5 Summary ...... 75

4 AGN Impact on Dwarf Galaxy Stellar Populations 81 4.1 Introduction ...... 81 4.2 Data and Analysis ...... 84 4.2.1 Star Formation History ...... 84 4.2.2 Mass Weighted Stellar Ages and Abundances ...... 87 4.3 Results and Discussion ...... 88 4.3.1 Are AGN suppressing star formation in isolated galaxies? ...... 90 4.3.2 The story behind counter-rotation ...... 91 4.3.3 Stellar Activity and Outflows ...... 94 4.4 Summary ...... 95

5 Summary and Conclusions 100 5.1 AGN are able to expel gas from dwarf galaxies ...... 100 5.2 AGN can affect global gas kinematics ...... 101 5.3 AGN with disturbed gas are associated with star formation suppression . . 102

A 105 A.1 Black Hole Masses ...... 105 A.2 Spatial Properties of Outflows ...... 106 A.3 Inclination Correction ...... 106 A.4 All rotation curves ...... 108

Bibliography 115

2 List of Figures

1.1 Figure 5 from the [47] Annual Review shows the discrepancy between pre-

dicted and observed stellar mass functions. The halo mass function predicted

by dark-matter-only simulations is denoted by the thick black line, and the

corresponding stellar mass function assuming a constant baryonic fraction

and star formation efficiency for each halo (M⋆ = ϵ⋆ fb Mhalo) is plotted

as a dotted black line. In comparison, the observed stellar mass function

of galaxies of [29] and [358] are shown as magenta stars and cyan squares,

respectively. The gray shaded region depicts a range of possible faint-end

slopes between α = −1.62 to −1.32. Note that the maximum star forma-

11 tion efficiency is reached in galaxies of roughly 10 M⊙, while star formation

becomes increasingly inefficient at the low- and high- mass end of themass

function...... 3

3 2.1 Top: BPT line ratios from the central 0.2 kpc of each galaxy for dwarf galaxies

in our sample observed with Keck/LRIS. 29 galaxies with optical signatures of

AGN were selected from the samples of RGG13, M14, and S15.The remaining

21 are a control sample composed of star-forming dwarf galaxies. Dwarfs that

present signatures of gas outflows are plotted with larger symbols. Bottom:

Redshift and stellar mass distribution of our sample of dwarf galaxies. . . . 15

2.2 SDSS color images of the 13 dwarf galaxies with spatially extended outflows.

All images were generated using the SDSS DR12 finding chart tool, with the

exception of NGC 1569, which is outside of the SDSS footprint. The NGC

1569 thumbnail is a PanSTARS z,g band color image rendered in the Aladin

Lite Viewer with a 3’ field of view (∼ 1 kpc on a side). Each SDSS image is

scaled to 10 kpc on a side and the placement of the 1 arcsecond-wide slit is

shown in light gray...... 16

4 2.3 Top: The spectrum of J084234.51+031930.7 is extracted from within R50

(gray). The pPXF best fit stellar continuum (red) is subtracted, leaving

the residual emission spectrum (black). The flux units in this figure are

(erg cm−2 s−1 Å−1). Middle: One- and two-component Gaussian fits to the

[O iii] doublet are shown. The one-component model on the left is clearly

a poor fit compared to the multicomponent fit on the right. The narrow

(green) and broad (orange) component color scheme is used throughout this

paper. Bottom: A close up of the outflow component of [O iii]λ5007 and

its W80 ∼ FWHM shaded in orange, indicating the outflow velocity (dashed

line) and escape velocity of this galaxy (dotted line)...... 20

2.4 Emission lines for J084234.51+031930.7 are shown as an example of how the

kinematic components can be decomposed and placed on the BPT diagram.

As described in Section 2.3.2 and illustrated in Fig. 2.3, the stellar continuum

is subtracted and the residual [O iii] doublet is fit using a double Gaussian

model which includes contaminating Fe i lines. The widths of Hα,Hβ, and

[N ii] are fixed based on the [O iii] model, but the fluxes for each kinematic

component are left as free parameters. The resulting line flux ratios for the

narrow (green star) and the broad component (orange circle) are plotted on

the BPT diagram (right). In this case, the model required an additional broad

Hα component, which was used to obtain a black hole mass (See Appendix A.1). 23

5 2.5 Narrow and broad emission line ratios are shown for each galaxy with out-

flows. The smaller symbols show the position of the bound gas (narrow

component in spectrum) for each galaxy, and the larger symbols those of the

outflow (broad component). In this paper, each galaxy is classified basedon

its position of the outflow component in the AGN (pink circles), composite

(gray diamonds), or star forming regions (cyan triangles)...... 25

2.6 Details of the broad component fits to the [O iii] doublets of each of the 13

galaxies with outflows are shown. The spectra are extracted from the region

within the R50 of each galaxy and have all been normalized by the continuum

flux just redward of [O iii]λ5007. AGN are grouped in the top figure and star

forming galaxies are on the bottom. Average fit parameters, weighted by the

luminosity of each narrow [O iii] line, are shown in the last panel of each

section. Panels shaded in gray are classified as composite and are excluded

from the AGN outflow average. Values of v0, W80, and vout are listed for

each of the 13 galaxies in Table 2.1...... 27

2.7 Spatial properties of the AGN-driven outflow in J090613.75+561015.5. The

outflow width W80 and offset v0 as defined in Section 2.3.4 as a function of

radius are shown in the top two panels, respectively. The ratio of the broad

to narrow [O iii] flux is shown in the bottom panel...... 30

6 2.8 A comparison between outflow component line profiles extracted from the

central ∼ 0.4 kpc and ∼ 1.5 kpc from the center of J090613.75+561015.5

is shown. We speculate that the central outflow appears blueshifted due

to denser material in the center of the galaxy obscuring emission from the

redshifted gas escaping the far side of the galaxy. Farther from the center,

the outflow profile widens and the velocity offset becomes less pronounced

as galactic obscuration fades and both blue- and redshifted portions of the

outflow is revealed...... 34

2.9 Relation between the velocity measured for the outflows and the modeled

escape velocity assuming galaxies live in massive dark matter halos consis-

tent with the cosmological picture of ΛCDM. In all cases, the wind speed is

comparable or above that needed to escape the dark matter halo. To guide

the eye, the dashed line indicates a 1-to-1 relation...... 35

2.10 The u − r model magnitude colors from SDSS DR 8 are plotted against

the MPA-JHU stellar mass. The colors are corrected for galactic extinction,

following [280] and the contours are from [278]. The photometry for NGC

1569 were measured in GALEX [124] and converted to SDSS ugriz via the

Python code pysynphot. The outflow symbol sizes are scaled to the fraction

of [O iii] flux contained in the outflows...... 38

7 3.1 Top: BPT diagnostic for all 50 galaxies in this sample. The dotted line

denotes the [163] classification cutoff, and the solid line is the [165] maximum

starburst line. Blue circles indicate isolated galaxies with disturbed gas and

with no neighbors of comparable mass (i.e. the neighboring galaxy is at least

0.75 times the stellar mass of the dwarf) within 1.5 Mpc (see Section 3.4.4).

Galaxies with counter-rotating stellar and gas components are marked as

orange triangles. Bottom:Stacked histograms of redshift and stellar mass of

the galaxies presented in this paper. Dark gray represents AGN hosts and

light gray represents star forming galaxies...... 49

3.2 colour images of all 50 dwarf galaxies in our sample. All images were gen-

erated using the SDSS DR12 finding chart tool, with the exception of NGC

1569, which is outside of the SDSS footprint. The NGC 1569 thumbnail (sec-

ond row, second column) is a PanSTARS z,g band colour image rendered in

the Aladin Lite Viewer with a 3’ field of view (∼ 1 kpc on a side). Each SDSS

image is scaled to 10 kpc on a side and the placement of the 1 arcsecond-wide

slit is shown in light gray...... 50

8 3.3 Pixel number along the spatial axis is shown on the x axis. The y axis shows

the signal to noise ratio of a featureless portion of the spectrum red-ward of

[O iii]λ5007. Moving along the slit, we summed pixel rows (black) until the

integrated spectrum’s signal to noise ratio (green) reached the target S/N

(red) or the maximum bin size was reached. The minimum bin size is 3

pixel rows, which sometimes results in even higher S/N. Exposure times for

each object were chosen with the intention of obtaining sufficient S/N in the

outskirts, so the bin size is dependent on the observational setup used. . . 56

3.4 Example ppxf fits to each of the three spectral sections used to determine

velocity curves. Each velocity curve consists of three components: stellar

(red), hydrogen (orange), and forbidden (purple, green, and blue)...... 59

3.5 The object J170639.14+334103.4 was chosen randomly from our sample to

provide an example of an orderly rotation curve, with a co-rotating disc of

gas and stars. The stellar (gray stars), Hβ (orange circles) and [O iii] (teal

circles) velocities are shown as a function of normalized radius, where r50

is the r-band Petrosian 50% radius. The dotted black line indicates the

expected velocity curve for an NFW profile with concentration parameter

c = 10. The shaded gray region represents the NFW curve expected from

halos with concentration parameter c = 8 − 15...... 61

9 3.6 Four stellar absolute circular velocity curves are shown to demonstrate the

variety of inner slopes found in our sample. Two examples of AGN are

displayed in the left panels and two star forming galaxies are shown on the

right. Dashed black lines and shaded gray regions represent NFW velocity

curves corresponding to a halo mass determined by abundance matching,

with the MPA-JHU stellar mass as input. Stellar velocity curves showing

agreement with the expected NFW profile are shown on the top two panels.

The velocity profiles in the bottom panels rise slowly, indicating cored dark

matter density profiles...... 62

3.7 We define ∆off to be the weighted absolute average of the velocity offset

between stars and gas, divided by the average absolute stellar velocity. This

metric is used to quantify the degree of separation between the stellar and

forbidden gas component. Based on the bimodal distribution of ∆off in our

sample, we consider galaxies ∆off >= 0.75 to have kinematically disturbed gas. 65

3.8 Examples of rotation curves where the gas is disturbed in different ways. In

some instances, gas is offset from the stars without showing any clear sign

of rotation (left). Some AGN have stratified narrow line components, where

the Balmer and forbidden lines are kinematically distinct from one another

(center). Five galaxies in our sample have gas and stellar discs rotating

separately, and sometimes in opposite directions (right)...... 66

10 3.9 The rotation curves for five galaxies with counter-rotating gas are shown

here. The colours are as in Figure 3.8, and the blue dots in the middle panel

indicate gas velocities measured from the [SII] doublet...... 69

3.10 Absolute line of sight velocity (vlos) measurements that far exceed the ex-

pected NFW velocity curves based on their stellar masses indicate overmas-

sive dark matter haloes relative to the measured stellar mass, implying ongo-

ing star formation suppression. Stellar (left), Balmer emission (center) and

forbidden emission (right) components are shown for the three galaxies in

our sample where this is most apparent. Green curves mark expected NFW

velocity curves for galaxies with stellar mass log(M⋆) = 10.5, 11, and 12 and

concentration parameter c = 10. Black dotted lines denote the expected

NFW velocity curves based on each galaxy’s MPA-JHU stellar mass. All

three of these galaxies host AGN, and two have counter-rotating gas compo-

nents, which lends additional evidence potentially associating AGN with gas

depletion and star formation suppression in dwarf galaxies...... 71

11 4.1 The ppxf fit to the integrated spectrum of a galaxy is shown. Thefully

reduced 2D spectrum is shown in the top panel, with the integrated region

highlighted in cyan. The middle panel displays the spectra integrated within

the highlighted cyan region (black), superimposed with the best fit stellar

(red) and gas (blue) model. Fit residuals are plotted in green. The third

panel shows the ppxf solution for across stellar age and metallicity intervals.

The regularized map shows the mass fraction of stars falling within each

interval, with higher mass fractions in yellow. The bottom panel plots the

stellar mass fraction over time, which traces the assembly history of the galaxy. 85

12 4.2 Top: The stellar mass growth is traced by the cumulative stellar mass fraction

over time. SFHs of all galaxies in the sample are shown as faint gray lines and

various groups of interest are highlighted in each panel. Top left: The red

lines represent the SFHs of six isolated galaxies with AGN. The AGN galaxies

with neighbors are indicated by brown lines and the SFHs for the star forming

control sample are shown as faint gray lines. Top middle: The five galaxies

in our sample with counter-rotating gas are emphasized. SFHs of counter-

11 rotating galaxies that are satellites of massive (M⋆ > 10 M⊙) galaxies are

shown as purple dotted lines, while isolated counter-rotating galaxy SFHs

are plotted in solid orange. Top right: Galaxies with outflows detected via

broadened [O iii] components are emphasized. SFHs for galaxies with AGN-

driven (pink), star formation-driven (blue), and AGN hosting galaxies with

star formation-driven outflows (composite; gray) are shown. Bottom: The

stellar mass - metallicity relation for active (blue) and passive (red) galaxies is

plotted [236]. In each bottom panel, the integrated stellar metal abundances

of the galaxies shown in the corresponding top panel are plotted according

to the same color schemes...... 89

13 4.3 The full mass weighted stellar age - stellar metallicity grids for all five counter-

rotating galaxies are shown, in order of increasing mass. The three galaxies

in the top row are satellites and the two in the bottom are isolated. Each

block in the grid is associated with a SSP with the specified stellar age and

metallicity. The color scheme represents the mass fraction associated with

each SSP, where yellow indicates the largest fraction...... 91

A.1 Spatially resolved properties of outflows are presented for the remaining 12

galaxies, as in Fig. 2.7. Consistent with the scheme used throughout this

paper, AGN-driven outflows are plotted with pink circles, star forming with

cyan triangles, and AGN with SF outflows with black diamonds. . . . 111

A.2 A diagram to illustrate how a disc with thickness c appears as an ellipse when

viewed from the inclination angle θinc. The inclination angle can be estimated

by measuring the ellipse semimajor and minor axes a, b and assuming the

disc thickness c...... 111

A.3 Twenty of the 45 galaxies with rotation curves have gas that rotates with the

stellar component. The shaded regions denote velocity curves following NFW

profiles, assuming concentration parameters between c = 8, 15. Galaxies

hosting AGN are shown in the top panel and star forming galaxies are in the

bottom...... 112

14 A.4 Twenty-five of the 45 galaxies with rotation curves have disturbed gas.See

Section 3.4.2 for a discussion on how we classify galaxies as disturbed. Galax-

ies hosting AGN are shown in the top group and star forming galaxies are in

the bottom...... 113

A.5 Eight of the 45 galaxies with rotation curves show stratification in their

emission lines. See Section 3.4.2 for a discussion on how we identify line

stratification. Line of sight velocity gradients are shown for J0811+23 and

J0842+03, as they are considered face-on based on their small inclination

angles (θ < 20◦) and thus are not corrected for inclination (as described in

Appendix A.4). Rotational velocity curves (corrected for disc inclination)

are shown for all other galaxies in this figure...... 114

15 List of Tables

2.1 Details of fits to spectra extracted within R50 of each galaxy, unless otherwise

specified. (1) Full SDSS names of all 13 galaxies with extended outflows (2)

Redshift (3) Stellar mass reported in the MPA-JHU catalog (4) Halo mass

determined via abundance matching using the method described in the text

and the stellar mass listed in (2) (5) Mean velocity of the outflow, in km s−1,

relative to the center of the narrow component (negative=blueshifted) (6)

Width containing 80% of the flux of the outflow component, inkms−1. (7)

− W80 −1 Outflow velocity defined as vout = v0 + 2 , in km s (8) Velocity required

to escape the dark matter halo (3) with an NFW profile from r = 0, in km s−1

(9) Fraction of [O iii] flux in the outflow, calculated as the ratio of thefluxin

the broad component, Fb, to the total flux in broad + narrow components,

Ftot (10,11) Decomposed BPT classifications for the bound and outflowing

gas. In order to optimize S/N, these fits were performed on spectra extracted

from customized apertures for each galaxy...... 44

16 3.1 LRIS configuration for each object, using the 1”slit placed along the semima-

jor axis of each galaxy. For the blue side (LRIS-B), we used the 600 groove

mm−1 grism blazed at 4000Å, yielding a dispersion of 0.63Å pixel−1. We

used three setups on the red side (LRIS-R):

A: 600 groove mm−1 grating blazed at 5000Å, 5600Å dichroic, yielding a

dispersion of 0.80Å pixel−1

B: 900 groove mm−1 grating blazed at 5500Å, 5600Å dichroic, yielding a

dispersion of 0.53Å pixel−1

C: 1200 groove mm−1 grating blazed at 7500Å, 5000Å dichroic, yielding a

dispersion of 0.40Å pixel−1 ...... 54

17 3.2 (1) * indicates objects excluded from this study. (2) Redshift is calculated

by fits to stellar absorption lines in LRIS spectra using ppxf. (3) Stellar

mass reported in the MPA-JHU catalogue. (4) b Black hole mass lower limits

derived using Eddington Luminosity arguments (M14) c Black hole mass

2 estimated using as MBH ∝ R∆V /G, where ∆V is measured from broad

Hα, extrapolating the BLR radius – luminosity relation extends into the

low mass regime (R13) (5) SDSS Petrosian radius containing 50% of r-band

flux, in kiloparsecs. (6) Classification of dominant ionization source basedon

Gaussian fits to emission lines using the process described in Section 3.3.2.

The spectra were extracted from the central 1kpc of each galaxy. (7) Same as

(6) but for HeII classification (S15) (8) Number of galaxies with comparable

mass within 1.5 Mpc. (9) Classified as disturbed (see Section 3.4.2) (10) Gas

is clearly rotating and offset from stellar component. (11) Has an outflow

identified by an additional broad component in as defined in Paper I.(12)

Narrow emission lines are stratified (see Section 3.4.2) ...... 77

3.3 Seven galaxies in our sample have disturbed gas kinematics and no neighbors

of comparable mass within 1.5 Mpc and ±1000 km s−1. Six of them host

AGN, two have counter-rotating gas, and four have outflows indicated by

broad wings in their [OIII]5007 emission line profiles. u − r colour is based

on SDSS cModelMag photometry...... 78

4.1 The average integrated mass-weighted stellar age, metal abundance, and for-

mation times for all 50 galaxies...... 99

18 Chapter 1

Introduction

The standard model of Big Bang cosmology ΛCDM model describes a universe consisting of three components: a cosmological constant denoted by Λ which describes dark energy, cold dark matter (CDM), and baryonic matter. Within this framework, primordial fluctuations seed large scale structure formation against an expanding background. Asover- dense regions collapse, they convert potential energy into kinetic energy and form virialized, dispersion-supported dark matter halos. Small halos collapse first, and merge together to form larger halos, building structure hierarchically. Pure dark matter (n-body) simulations provide a well-defined set of predictions about the numbers, clustering, and structure of dark matter halos [184]. The ΛCDM model is the simplest model that fits experimental observations of abundances of primordial elements (e.g. [35]), the structure and existence of the cosmic microwave background (e.g. [234, 171]), and large scale structure formation

(e.g. [34]).

1 Baryons, which were well-mixed with dark matter in the early universe, collapse along with the dark matter halos. During this collapse, baryons cool via radiative processes and sink to the center of their dark matter halos, forming rotationally-supported gas disks.

Stars then form from cool gas within these disks, resulting in galaxies with stellar, gas, and dark matter components. Generations of stars enrich their surroundings with heavy elements produced throughout their lives and at the moment of their deaths. These com- pounds produced within stars provide the conditions for life to arise, so understanding the origin of stars, and the galaxies in which they form, is fundamental to understanding our own existence.

1.1 Small Scale Problems

The ΛCDM model successfully describes conditions necessary to produce the large scale structure we observe today, but discrepancies between theory and observation arise on small scales. Assuming each dark matter halo has a constant fraction of baryons, fb, and that those baryons are converted into stars with the same efficiency, ϵ⋆, across all mass scales, one would expect stellar mass to scale linearly with halo mass. However, as shown in

Figure 1.1, the predicted halo mass function deviates significantly from the observed stellar mass function. Maximum star formation efficiency is achieved at roughly the stellar mass

11 of the Milky Way (M⋆ ≈ 10 M⊙), while efficiency drops dramatically in the high- and low- mass ranges. This observed inefficiency, or suppression of star formation, particularly at the low-mass end of the mass function, is a topic of great interest in the field of galaxy evolution, and is known as the ‘missing satellites problem’ [354, 22, 290].

2 Figure 1.1: Figure 5 from the [47] Annual Review shows the discrepancy between predicted and observed stellar mass functions. The halo mass function predicted by dark-matter- only simulations is denoted by the thick black line, and the corresponding stellar mass function assuming a constant baryonic fraction and star formation efficiency for each halo (M⋆ = ϵ⋆ fb Mhalo) is plotted as a dotted black line. In comparison, the observed stellar mass function of galaxies of [29] and [358] are shown as magenta stars and cyan squares, respectively. The gray shaded region depicts a range of possible faint-end slopes between α = −1.62 to −1.32. Note that the maximum star formation efficiency is reached in galaxies 11 of roughly 10 M⊙, while star formation becomes increasingly inefficient at the low- and high- mass end of the mass function.

3 The clustering of CDM can be approximated at all masses by a simple formula known as the NFW profile, after Navarro, Frenk & White [219]. The NFW profile is characterized by a density profile that rises steeply at small radius, otherwise knownas a cusp. However, observed dwarf galaxy rotational velocity profiles show a wide diversity of inner slopes, some of which rise linearly with radius [227]. These slowly rising rotation curves imply constant, underdense dark matter profiles in the galaxy centers, otherwise known cores. This disparity between simultated and (some) observed dwarf galaxies is know as the ‘cusp vs. core’ problem, which has remained unsolved for decades.

Finally, the ‘too big to fail’ problem arises due to a shortage of galaxies with central

10 densities indicative of halos of roughly 10 M⊙. Such massive halos are believed to be too

6 massive not to have formed stars, and the corresponding stellar mass of 10 M⊙ is likely

too small for baryonic processes to disrupt the dark matter halo. This stellar mass range

where this problem arises is beyond the scope of this study, but a detailed review of the

challenges to the ΛCDM paradigm can be found in this detailed review [47].

These departures from the ΛCDM model have prompted some to look into warm

(e.g. [193]) or self-interacting dark matter (e.g. [253]). A promising alternative to re-

thinking the nature of dark matter is to investigate the effects of baryonic feedback on star

formation.

4 1.2 An Overview of Baryonic Feedback

A large amount of theoretical work has been done to understand the complex processes at work within galaxies, and has led to a wide variety of feedback models to consider. Careful observational measurements place valuable constraints on theoretical models and are necessary to fully understand the role of feedback in shaping dwarf galaxies.

1.2.1 Stellar feedback

High resolution simulations explore the effects of baryonic processes on dark matter halos and conclude that stellar processes are capable reconciling observed properties of dwarf galaxies with ΛCDM [350]. Bulk gas motions driven by bursty stellar feedback can cause fluctuations in the galaxy’s gravitational, resulting in transformation from central dark matter cusps into cores [202, 127]. In these simulations, the removal of material from the galactic centers relies on strong outflow events, triggered by bursty star formation histories.

Theoretical work also attributes star formation suppression in dwarf galaxies to heating and outflows driven by supernovae and stellar winds (e.g. [103, 150]). This scenario is supported by a large amount of observational evidence. Powerful outflows driven by star formation are observed in starbursting galaxies [198, 302], and it is often suggested that stellar feedback dominates in the dwarf regime [200].

1.2.2 AGN feedback

However, stellar feedback is not the only mechanism capable of influencing galaxy evolution. A large body of evidence supports the widely held notion that supermassive black

5 holes (SMBH) live at the centers of all massive galaxies, suggesting that they are directly connected to galaxy assembly (e.g. [296, 37]). Tight scaling relations between SMBH mass and large scale galaxy properties such as bulge mass and stellar velocity dispersion imply that the growth and evolution of SMBH and their host galaxies are linked. Energetic winds are often invoked to explain the connection between BH mass and galaxy properties far beyond the BH’s gravitational influence. These winds are said to originate when theSMBH accretes material, which sheds its gravitational potential energy by radiative processes. At this point, the SMBH is referred to as an active galactic nucleus (AGN). Winds driven by AGN are thought to either heat or disperse cold gas, shutting down star formation in a process known as negative feedback. Alternatively, positive feedback might occur when these winds compress cold gas clouds and activate star formation.

These processes are extensively studied in high mass systems, but are not very well

10 understood on the small scale. Dwarf galaxies (M⋆ ≤ 10 M⊙) have shallow gravitational

wells which offer an ideal laboratory for studying various feedback processes. Adeeper

understanding of AGN activity in these environments will place valuable constraints on

theoretical models of galactic feedback and extend our understanding of AGN processes

into the low mass regime. Furthermore, dwarf galaxies are the building blocks of massive

galaxies, meaning that understanding the processes that govern star formation in dwarfs is

fundamental to understanding galaxy evolution as a whole.

Due to their small masses, BHs in dwarf galaxies are observationally difficult to

study. As a result, AGN activity on dwarf galaxy scales has been largely unexplored until

recently. Optical and IR signatures of hundreds of AGN candidates have been reported in

6 the last few years [249, 209, 273, 9, 31]. In fact, the infrared (IR)-selected AGN fraction

8−10 is predicted to be 10 − 30% in galaxies in the stellar mass range M⋆ ∼ 10 M⊙, an order of magnitude higher than the established fraction in higher mass galaxies (1 − 3%

11 for M⋆ > 10 M⊙)[164]. Since there are several factors that hinder the detection of AGN in dwarf galaxies, this fraction can be regarded as a lower limit [275, 58]. Furthermore, observational evidence of AGN-driven outflows is rapidly accumulating [238, 41, 93, 195].

In the face of these new observations, it is becoming increasingly difficult to ignore the potentially important effects of AGN feedback in dwarf galaxy evolution.

1.3 This Work

This thesis project utilizes high resolution, spatially resolved spectroscopic observations of 50 dwarf galaxies with and without optical and IR signatures of AGN to investigate the potential for AGN to influence their low-mass hosts. We find several linesof evidence supporting the ability of AGN to effect large scale changes on their host galaxies in the dwarf regime. In Chapter 2, we report the first direct detection of AGN-driven ionized gas outflows in dwarf galaxies. We carefully measure the gas kinematics and showthat the gaseous outflows have sufficient velocity to escape their hosts’ dark matter halos.In

Chapter 3, we decompose galaxy kinematics into stellar and ionized gas components and analyze the various processes that can produce disturbed gas kinematics. In Chapter 4, we trace the star formation histories for each galaxy and discuss how various feedback processes are reflected in the observed stellar properties. Throughout this project, weassume

−1 −1 the cosmological model H0 = 71 km s Mpc , Ωm = 0.27, and ΩΛ = 0.73.

7 Chapter 2

Outflows

We present spatially resolved kinematic measurements of AGN-driven outflows in

8 9 dwarf galaxies in the stellar mass range ∼ 6 × 10 − 9 × 10 M⊙, selected from SDSS DR7,8

and followed up with Keck/LRIS spectroscopy. We find spatially extended (∼ 1 half light

−1 radius), high velocity ionized gas outflows (W80 up to ∼ 2000 km s ) in 13/50 dwarf galaxies

with and without AGN. Nine of the galaxies with outflows have optical line ratios indicative

of AGN, and six of these have outflow components with optical line ratios also consistent

with AGN ionization. Outflow velocities in all 13 galaxies exceed the escape velocities of

their halos. Nine of these 13 galaxies are classified as AGN according to their narrow line

flux ratios. Of these, six have outflow components with emission line ratios consistent with

AGN ionization. Although black holes have been known to populate the centers of at least a

few dwarf galaxies, and indirect evidence of AGN quenching of star formation in dwarfs has

begun to surface, our measurements constitute the first direct detection and measurement of

AGN impact on the large scale kinematics and gas content in dwarf galaxies. Furthermore,

8 we find evidence suggestive of ongoing star formation suppression, possibly regulated by the AGN. Galaxy formation models must therefore be able to account not only for the formation and growth of black holes at the centers of dwarf galaxies, but should also be revised to include AGN as important – and perhaps dominant – sources of feedback in low mass galaxies.

2.1 Introduction

Well established correlations between black hole (BH) masses and global galactic properties imply a scenario where the growth and evolution of a BH and its host galaxy are connected and regulated by feedback from the active galactic nucleus (AGN) (e.g., [174]).

In massive galaxies, the presence of AGNs has been shown to be linked to the development of powerful gas outflows (e.g., [140, 204, 64, 258]), which are a vital ingredient ofgalaxy formation models within the cosmological framework of Λ Cold Dark Matter (ΛCDM), as they regulate and suppress star formation [329, 279, 98, 241] and bring the luminosity function of galaxies into agreement with the predicted dark halo mass function [75, 212].

10 In the mass regime of dwarf galaxies (M∗ < 10 M⊙), a large body of theoretical

work attributes the regulation of star formation solely to reionization and stellar feedback,

by means of radiation from young stars and supernova explosions [23, 37]. In fact, powerful

outflows driven by star formation have been observed in starbursting dwarfs such asM82

[198, 302]. Further observational evidence suggests that supernova feedback is likely to

dominate in dwarfs [200]. Quenched dwarf galaxies are rare, and the vast majority of them

are found within 4 virial radii of a larger galaxy (MK < −23) [122], so environmental

9 effects are likely largely responsible for gas removal from low mass galaxies. However,a small number of isolated dwarf galaxies are observed with no signs of recent star formation

[154], showing that processes internal to dwarf galaxies cannot be ruled out as quenching mechanisms. Interestingly, evidence of AGN via optical and infrared (IR) indicators has been detected in hundreds of nearby dwarf galaxies [247, 209, 273]. [164] report the IR- selected AGN occupation fraction in high mass galaxies to be 1−3%, while the same criteria

8−10 yield a 10 − 30% fraction in dwarf galaxies (M∗ ∼ 10 M⊙). Given that there are several factors that hinder the detection of AGN in dwarfs [275, 58], this large AGN fraction can be regarded as a lower limit. These studies suggest that AGN are common and potentially important phenomena in the low mass regime.

The role of AGN feedback in dwarf galaxy evolution is being explored theoretically, with diverse results. In idealized environments and using simplifying assumptions, such as spherical symmetry and single-phase ISM, [85] find that AGN can be more efficient than star formation at clearing dwarf galaxies of their gas. [175] explore a range of photoionization models and outflow geometries in isolated dwarfs, concluding that AGN are unlikely to regulate star formation but can boost the energetics of existing stellar-powered outflows.

Cosmological simulations considering AGN feedback in high-z dwarf galaxies indicate that

BHs can provide a significant amount of feedback, able to effectively quench star formation

[13] and potentially reconcile observed dwarf galaxy anomalies with ΛCDM predictions

[284]. Conversely, [313] find that even in the most extreme BH growth scenario, AGN feedback is negligible in comparison to ionizing starlight. In fact, they find that supernovae feedback stunts BH growth and quenches AGN feedback. This wide variation in theoretical

10 results demonstrates the need for observational constraints on the coupling of AGN energy to the interstellar medium (ISM) of dwarf galaxies.

Encouragingly, observational evidence of AGN feedback in dwarf galaxies is be- ginning to surface. In a study of 69 quenched dwarf galaxies from the MANGA survey

[49], [238] find hints of a correlation between low star formation activity and thepres- ence of AGN. Six quenched galaxies in their sample show signs of AGN, and five of their six AGN candidates show ionized gas kinematically decoupled from their stellar velocity fields, suggestive of either outflows or recently accreted gas. Additionally, [41] havefound gas-depleted isolated dwarf galaxies with optical line ratios consistent with AGN, and [93] report AGN-like line ratios in a majority of the quiescent galaxies in their sample.

These promising results challenge current conceptions of feedback in dwarf galaxies and raise the question of whether the gas escapes the dark matter halo, permanently exhausting star formation in the galaxy, or stalls in the halo to cool and fall back later as part of a cycle of active and quiescent phases in a dwarf galaxy’s life. This will ultimately depend on the mass removed by the outflow and its relative velocity compared to the velocity needed to escape the combined gravitational pull of the dwarf galaxy and its dark matter halo.

Additionally, dwarfs are expected to have a lower merger rate and a more quiet merger history than more massive galaxies [255], making their BHs closer relics of the initial

BH seeds from which they originated (e.g., [324]). If AGN feedback influences the growth of BHs in dwarf galaxies, these objects will not be useful tracers of the seed BH population, and will have significant implications for BH seed formation models [206].

11 A complete understanding of AGN feedback will rely on thorough investigations of outflows affecting all phases of the interstellar medium (e.g. [67]). In the meantime, direct detection and measurement of any AGN-driven outflows in dwarf galaxies will be a crucial first step. In this work, we examine a sample of mostly isolated dwarf galaxies, both with and without optical and IR signs of AGN activity. We directly detect, measure and characterize ionized gas outflows in 13 dwarf galaxies and report the first velocity measurements of AGN-driven outflows in this mass regime.

We present our sample selection and observations in Section 2.2. We describe our fitting methods and kinematic analysis in Section 3.3, with the criteria foroutflow detection presented in Section 2.3.3. We present the results of our fits in Section 2.4, provide our physical interpretation of our results in Section 2.5, and summarize in Section 2.6.

−1 −1 Throughout the paper we assume the cosmological model H0 = 71 km s Mpc , Ωm =

0.27, and ΩΛ = 0.73.

2.2 Data

2.2.1 Sample Selection

Drawing from the Sloan Digital Sky Survey Data Releases 7 and 8 (SDSS DR7,8),

[247], [209], and [273] (hereafter RGG13, M14, and S15, respectively) have identified hun-

10 dreds of nearby (z < 0.1) dwarf (M∗ < 10 M⊙) galaxies that exhibit optical and IR

signatures of AGN. RGG13, M14, and S15 selected their samples using standard optical

emission line diagnostics which probe the hardness of the dominant ionizing source. RGG13

identified 151 AGN candidates using the Baldwin, Phillips & Terlevich (BPT) diagnostic

12 [11] and the presence of broad Hα emission lines. M14 also drew from SDSS and used the

BPT, He ii, [S ii], and [O i] AGN indicators to build their sample. They imposed further

distance and photometry cuts in order to probe the low luminosity regime, resulting in a

sample of 28 AGN. S15 extended the number of AGN candidates significantly (336) by

including sources which have He ii emission and redder mid-IR colors consistent with AGN

[155, 299]. Due to their similar selection criteria, there is significant overlap between these

three parent samples.

From the parent samples of RGG13, M14, and S15, we selected candidate AGN

host galaxies for follow-up study based on (1) emission line ratios falling above the star

forming sequence [163] on the BPT diagram and (2) presence of the high ionization He ii

emission line [282]. Priority was given to spatially extended galaxies, and face-on galaxies

were excluded whenever possible, to facilitate spatially resolved kinematic and emission line

diagnostic measurements. Other than this, galaxies were selected from the subsample based

on the right-ascensions that could be observed during our observing time. The resulting

observed sample contained 29 galaxies with optical signatures of AGN activity (Fig. 2.1).

Fifteen of the AGN in our sample were selected from RGG13, an additional nine only from

M14, and five more only from S15.

A control sample of galaxies with no optical or IR signatures of AGN was selected

from the OSSY catalog [223], which provides spectral line analysis for the entire SDSS DR7

atlas. We matched the sample with the MPA-JHU catalog [44, 163, 314], in order to obtain

stellar masses. We applied the same redshift and stellar mass cuts as the AGN sample and

excluded all galaxies falling above the star forming sequence on the BPT diagram, as well as

13 all galaxies with detectable He II [282]. We also excluded potential AGN based on the WISE mid-IR color criteria [155, 299]. From this parent sample, we selected spatially extended galaxies to match the characteristics of the AGN sample. NGC 1569 was included specifically to facilitate comparison with previous kinematic studies [197]. The resulting sample of 21 star-forming dwarf galaxies were those with coordinates that could be observed during the

Keck observing runs. BPT line ratios from the central 0.2 kpc and corresponding redshift and mass distributions of our targets are shown in Fig. 2.1. The full sample is described in detail in Chapter 3.

Note that the control sample could potentially contain AGN that elude the selection criteria we used. Several factors can hinder the detection of AGN in dwarf galaxies, including dilution by the host galaxy (e.g. [210]), low metallicity [166], and AGN variability

[189]. In each case, the qualitative effect is to obscure existing AGN signifiers.

2.2.2 Observations and Data Reduction

We obtained longslit spectroscopy of the 50 targets using the Low Resolution

Imaging Spectrometer (LRIS;[226, 50]) on the Keck I telescope on the nights of UT 2015

March 24–25, December 4–5, and 2017 June 24–25. We placed a 1 arcsecond-wide slit along the semimajor axis (see Fig. 3.2) of each galaxy, projecting to ∼ 7 pixels on both the blue and red CCDs (Marconi on LRIS-B and LBNL on LRIS-R). The objects in our sample are located at distances between 3 and 209 Mpc (z < 0.05), which yield spatial scales between

14 and 965 pc arcsec−1 [359]. For the blue side (LRIS-B), we used the 600 groove mm−1

grism blazed at 4000Å, yielding a dispersion of 0.63Å pixel−1. For the red side we used

14 1.5

) 1.0 β H / ] I

I 0.5 I O [ AGN with outflows ( g

o 0.0 AGN with SF outflows l SF with outflows 0.5 no outflows 2.0 1.5 1.0 0.5 0.0 0.5 log([NII]/Hα)

12 12 10 10 8 8 6 6 AGN 4 4 2 2 Star forming Number of Galaxies 0 0 0.01 0.03 0.05 8.5 9.0 9.5 10.0 z log(M /M ) ∗ ¯

Figure 2.1: Top: BPT line ratios from the central 0.2 kpc of each galaxy for dwarf galaxies in our sample observed with Keck/LRIS. 29 galaxies with optical signatures of AGN were selected from the samples of RGG13, M14, and S15.The remaining 21 are a control sample composed of star-forming dwarf galaxies. Dwarfs that present signatures of gas outflows are plotted with larger symbols. Bottom: Redshift and stellar mass distribution of our sample of dwarf galaxies.

15 N

AGN

Star Forming

Figure 2.2: SDSS color images of the 13 dwarf galaxies with spatially extended outflows. All images were generated using the SDSS DR12 finding chart tool, with the exception of NGC 1569, which is outside of the SDSS footprint. The NGC 1569 thumbnail is a PanSTARS z,g band color image rendered in the Aladin Lite Viewer with a 3’ field of view (∼ 1 kpc on a side). Each SDSS image is scaled to 10 kpc on a side and the placement of the 1 arcsecond-wide slit is shown in light gray.

16 either the 600 groove mm−1 grating blazed at 5000Å, the 900 groove mm−1 grating blazed at 5500Å, with a 5600Å dichroic, or the 1200 groove mm−1 grating blazed at 7500Å, with a 5000Å dichroic, yielding dispersions of 0.80, 0.53, and 0.40Å pixel−1, respectively. We obtained one or two 1200 second exposures of each galaxy. To achieve the signal to noise ratio necessary for proper fitting of the spectra, a second exposure was necessary for galaxies with surface brightness > 21.5 mag arcsec−2. The weather was clear on all six nights, and the seeing was typically under 0.6 arcsec, except on UT 2015 March 24, when it was 0.7 arcsec. For details of observations of individual objects see Chapter 3. The data were reduced using a Python pipeline to automate the standard IRAF reduction tasks. Flexure on the red camera was corrected using the average shift in sky lines. There are not enough sky lines to correct for flexure on the blue CCD, so each galaxy spectrum on the blueside was redshift-corrected using the redshift measured from the flexure-corrected red spectrum.

Flexure on the blue CCD was then calculated by comparing galaxy emission lines with their expected rest frame values. The longslit spectra were rectified along both the wavelength and spatial axes, creating 2-dimensional spectra where each pixel row is a fully reduced

1-dimensional spectrum. Customized extractions along the slit are obtained by summing pixel rows, allowing us to preserve spatial information by extracting small sections of the spectra or to sum over large apertures when higher signal to noise is required.

2.3 Analysis

Visual inspection of the emission line profiles of the galaxies in our sample revealed clear broadened, often blueshifted wings in some of the galaxies. Such line profiles are often

17 indicative of gas outflows. Thus, in order to systematically search for outflows in our sample, we conducted a detailed and consistent fitting process as described below.

2.3.1 Fitting the Stellar Continuum

For each of the 50 galaxies in our extended sample, we used the same fitting algorithm to systematically identify and measure outflows. For each source, we began by extracting a one-dimensional spectrum of the entire galaxy, when possible. Some galaxies in our sample have contaminating foreground stars, in which case we chose custom apertures to maximize the extraction region while excluding the contaminating sources.

In order to measure accurate emission line fluxes, it is necessary to account for stellar absorption, which primarily affects the Balmer emission lines. Penalized Pixel-Fitting method (pPXF) [59] is an algorithm designed to extract stellar kinematics using a maximum penalized likelihood approach to match stellar spectral templates to absorption features in galaxy spectra. In order to minimize template mismatch, stellar templates with relevant stellar types, negligible emission line contamination, and full wavelength coverage for the wavelength range in our galaxy spectra were chosen from the Indo-US Library of Coudé

Feed Stellar Spectra [318]. pPXF is designed to choose the appropriate stellar templates automatically, but it is necessary to check that emission line contamination from the ISM in the templates does not skew the fit, ultimately resulting in underestimation of Balmer emission line fluxes. Visual inspection of the fit to features such astheCa ii λ3933 line, which is free from contaminating emission lines, allows us to assess whether the stellar continuum and absorption features are being properly estimated. An example of a fit to the stellar spectrum of a galaxy is shown on the top panel of Fig. 2.3. Careful selection of

18 stellar templates is especially important for young stellar populations, whose fits are often much improved by considering only B and A-type stellar templates in order to carefully fit their prominent Balmer absorption features.

2.3.2 Fitting Emission Lines

general isolation from other strong spectral features, we used the [O iii] λλ4959,5007 doublet to constrain line profiles for the rest of the emission lines in the spectra. The middle panels of Fig. 2.3 show that a single Gaussian produces a poor fit when broadened wings are visible in the [O iii] doublet. To address this, we constructed a double-Gaussian model consisting of a narrow and a broad component. In order to reduce the number of free parameters in the

[O iii] line profile fit, we placed three constraints on each Gaussian component: (1)Based on transition probabilities, the flux ratio between [O iii]λ4959 and [O iii]λ5007 was fixed to

1:3; (2) the velocity widths derived from each Gaussian component were forced to be equal in both emission lines in the doublet; (3) the spacing between the emission lines was held fixed at 2869.35 kms−1 or 47.92Å. Fe i λ4985, 4986, 5016 lines contribute a small amount of additional flux which causes the fit to overestimate the width of the broad component.To address this contamination, we model them with independent amplitudes and widths equal to that of the narrow component of [O iii]. The following were left as free parameters: (1,2)

Amplitudes of narrow and broad components; (3,4) velocity widths of narrow and broad

19 80 70 60 λ

F 50

x 40 u

l 30 F 20 10 0 4000 4500 5000 [O III] 1 Component [O III] 2 Components 160 160 140 χ2 = 12647. 17 140 χ2 = 92. 95 120 120

λ 100 100 F

, 80 80 x 60 60 u l 40 40 F 20 20 0 0 20 20 5050 5080 5110 5140 5170 5050 5080 5110 5140 5170 λ(Å) λ(Å) 70 t c s u

60 e o v v λ 50 F

, 40 x

u 30 l

F 20 10 0 -750 -500 -250 0 250 500 1 v (km s− )

Figure 2.3: Top: The spectrum of J084234.51+031930.7 is extracted from within R50 (gray). The pPXF best fit stellar continuum (red) is subtracted, leaving the residual emission spectrum (black). The flux units in this figure are (erg cm−2 s−1 Å−1). Middle: One- and two-component Gaussian fits to the [O iii] doublet are shown. The one-component model on the left is clearly a poor fit compared to the multicomponent fit on the right. The narrow (green) and broad (orange) component color scheme is used throughout this paper. Bottom: A close up of the outflow component of [O iii]λ5007 and its W80 ∼ FWHM shaded in orange, indicating the outflow velocity (dashed line) and escape velocity of this galaxy (dotted line).

20 components; (5) recession velocity of the doublet, set by the mean velocity of the narrow component of [O iii]λ5007; (6) velocity offset between narrow and broad components; and

(7-9) amplitudes of contaminating Fe i lines.

2.3.3 Detecting Outflows

Broadened or shifted components in emission lines trace gas with different kine-

matics than the rest of the ionized gas in the galaxy. Such components potentially trace

outflowing gas. In order to systematically detect outflows, we fit both single anddouble

Gaussian models to the [O iii] doublet in each of the 50 galaxies in our sample. Fits were

performed on one-dimensional spectral extractions covering as much of each galaxy as pos-

sible, as described in Section 3.3.3. Details of the double Gaussian models are described in

Section 2.3.2 and examples of the single- and double-component fits are shown in the two

middle panels of Fig. 2.3.

An additional Gaussian component always reduced the χ2 of the fits, so a rigid

goodness-of-fit threshold to determine whether a line requires a second Gaussian would

not yield robust results. Instead, we flagged each fit that produced a second kinematic

component wider than the instrumental resolution (σ > 80 km s−1) and amplitude higher

than the noise level of the spectrum. This approach yielded a subsample of 15 candidate

outflow galaxies.

Next, we examined the spatial extent of these broad components by repeating the

double Gaussian fits on smaller extraction regions along the slit in each of the 15galax-

ies. We found that the broad [O iii] components in two AGN-hosting galaxies, J094941.20

+321315.9 and J141208.47+102953.8 are spatially unresolved. The remaining 13 galaxies,

21 however, show clear broadened components in their [O iii] at all radii, as long as the emission line was detectable (typically out to one half light radius, or ∼ 1 − 3 kpc). Based on their narrow component emission line ratios, nine of these 13 galaxies with spatially resolved broad components are classified as AGN and four are star forming (SF). Full names, redshifts, stellar masses, and narrow line BPT classifications for these 13 outflow galaxies are listed in Table 2.1.

Of our full sample of 50 galaxies, 31% (9/29) of the AGN and 19% (4/21) of the

SF galaxies show spatially extended outflows. If we include the two AGN with spatially unresolved broad components, we observe outflows in 38% of the AGN in our sample.

2.3.4 Outflow Velocity

Table 2.1 lists fit outputs to one-dimensional spectrum extractions within ther- band Petrosian half light radius (hereafter R50) of each of the 13 galaxies discussed in this work. W80, the velocity width containing 80% of the flux of an emission line, is a widely used metric to describe outflow velocities [140]. For a single Gaussian profile, W80 = 1.09 FWHM.

We define the outflow velocity

W v = −v + 80 (2.1) out 0 2

where v0 is the velocity offset between the center of the narrow and broad components (see Fig. 2.3) and is negative when blueshifted.

22 Hβ [OIII] Hα, [NII] ) 1.5 1 − 14.0 70 60.0 Å

1 1.0 − 12.0 60 50.0 s )

2 β

− 10.0 50 40.0 H 0.5 m / c ]

8.0 40 I g I r 30.0 I e

( 0.0 30

6.0 O 7 [ 1

20.0 ( −

20 g

0 4.0 o

1 0.5 l λ 10.0

F 2.0 10

, x

u 0.0 0 0.0 1.0 l F 4940 4950 4960 4970 4980 5060 5095 5130 5165 5200 6694 6723 6751 6780 6809 2.0 1.5 1.0 0.5 0.0 0.5 1.0 wavelength, λ(Å) wavelength, λ(Å) wavelength, λ(Å) log([NII]/Hα)

Figure 2.4: Emission lines for J084234.51+031930.7 are shown as an example of how the kinematic components can be decomposed and placed on the BPT diagram. As described in Section 2.3.2 and illustrated in Fig. 2.3, the stellar continuum is subtracted and the residual [O iii] doublet is fit using a double Gaussian model which includes contaminating Fe i lines. The widths of Hα,Hβ, and [N ii] are fixed based on the [O iii] model, but the fluxes for each kinematic component are left as free parameters. The resulting line flux ratios for the narrow (green star) and the broad component (orange circle) are plotted on the BPT diagram (right). In this case, the model required an additional broad Hα component, which was used to obtain a black hole mass (See Appendix A.1).

2.3.5 Decomposed Flux Ratios

In most of the galaxies discussed here, the broad emission line component can be detected in several emission lines. When possible, we applied the two-component kinematic [O iii] model to Hα,Hβ, and[N ii] in order to place the outflowing gas on the BPT diagram. The kinematic model (velocity offsets and widths) measured in[O iii] are held fixed while the amplitudes of each kinematic component are allowed to vary independently.

Due to their small separations, Hα and the [N ii] doublet were fit simultaneously, with the flux ratio of [N ii]λ6548 and [N ii]λ6563 fixed at 1:3 in accordance with their transition probabilities. Two galaxies (J084234.51+031930.7 and J100935.66+265648.9) required an additional broad Hα component in order to constrain the outflow Hα /[N ii] flux ratio. See

Appendix A.1 for further discussion on additional broad Hα components associated with the broad line region (BLR). The full multicomponent fits to Hβ, [O iii], Hα, and [N ii]

23 as well as the resulting kinematically decomposed BPT ratios for J084234.51+031930.7 are shown in Fig. 2.4.

2.4 Results

2.4.1 Classifying Outflows

In Fig. 2.5, we show the position of the narrow and broad components (small and large symbols, respectively) on the BPT diagram, obtained following the procedure described in Section 2.3.4. The two components for each galaxy are connected by a thin line of the same color.

The star forming galaxies (cyan triangles) were included in our control sample due to their narrow components’ positions on the BPT star forming sequence. Two of the SF objects (J101440.21+192448.9 and J130724.63+523715.2) are from the RGG13 sample of

BPT star forming galaxies with broad Hα lines. Follow-up observations of these two objects found that these broad Hα features were transient and likely due to Type II supernovae

(also confirmed by our observations [8]). The outflows in all four galaxies fall withinthe star forming region of the BPT diagram.

Emission line ratios falling above the [163] (dotted) line are widely regarded as evidence of AGN activity. However, a well known limitation of the BPT diagram in definitively identifying AGN is that shock ionization with significant contribution from precursor gas can produce line ratios in star forming galaxies that mimic those of AGN [4]. Strong near

IR detections of the [Si vi] coronal line provide independent confirmation of the presence

24 1.5

1.0

) J0840+18 β H / ]

I 0.5 I I O [ ( g o l 0.0 AGN with outflows AGN with SF outflows SF with outflows Kewley '01 0.5 Kauffmann '03 2.0 1.5 1.0 0.5 0.0 0.5 log([NII]/Hα)

Figure 2.5: Narrow and broad emission line ratios are shown for each galaxy with outflows. The smaller symbols show the position of the bound gas (narrow component in spectrum) for each galaxy, and the larger symbols those of the outflow (broad component). In this paper, each galaxy is classified based on its position of the outflow component intheAGN (pink circles), composite (gray diamonds), or star forming regions (cyan triangles).

25 of AGN in four of the dwarfs with outflows (J090613.75+561015.5, J095418.16+471725.1,

J100551.19+125740.6, and J100935.66+265648.9; Bohn et al., in prep). Near IR line ratio diagnostics confidently exclude shocks as the originating ionizing mechanism inthese objects. The [Ne v]λ3426 coronal line is also detected in these four AGN as well as

J084025.54+181858.9. These measurements provide additional evidence for the presence of AGN at least in these five objects. In this work, we classify the nine objects with narrow emission lines above the dotted [163] line as AGN.

Six dwarfs with AGN have broad components that occupy the region above the

[165] maximum starburst line (solid) on the BPT diagram, so we plot them as pink circles throughout this paper. J084025.54+181858.9 did not have a sufficiently high signal-to-noise ratio to fit the outflow in lines other than [O iii], so we count this object among the AGN- driven outflow sample based on its AGN-consistent narrow emission line ratios. Two ofthe

AGN (gray diamonds) have outflow components that fall in the composite region, indicating a significant contribution from star formation.

Throughout this paper, we classify each outflow based on position of the broad component on the BPT diagram. Table 2.1 is sectioned according to the broad component

BPT classification and lists the BPT classification for both narrow and broad components in the last two columns.

2.4.2 Integrated Properties of Outflows

In Fig. 2.6, we illustrate the difference in line profiles between galaxies withand without AGN. The galaxies are grouped according to the classification assigned in Sec-

26 0.5

0.4

0.3

0.2 Relative Flux

0.1

0.0

0.5 AGN Average 2.0

0.4 1.5 0.3 1.0 0.2 Relative Flux 0.1 v = 106 km/s 0.5 0 − 0.0 W80 = 1160 km/s 0.0 4925 4975 5025 4925 4975 5025 4925 4975 5025 4925 4975 5025 -1000 -500 0 500 1000 1 λ (Å) λ (Å) λ (Å) λ (Å) v (km s− )

0.5 SF Average 2.0

0.4 v0 = 8 km/s 1.5 0.3 W80 = 1387 km/s 1.0 0.2 Relative Flux

0.1 0.5

0.0 0.0 4925 4975 5025 4925 4975 5025 4925 4975 5025 4925 4975 5025 -1000 -500 0 500 1000 1 λ (Å) λ (Å) λ (Å) λ (Å) v (km s− )

Figure 2.6: Details of the broad component fits to the [O iii] doublets of each of the 13 galaxies with outflows are shown. The spectra are extracted from the region withinthe R50 of each galaxy and have all been normalized by the continuum flux just redward of [O iii]λ5007. AGN are grouped in the top figure and star forming galaxies are onthe bottom. Average fit parameters, weighted by the luminosity of each narrow [O iii] line, are shown in the last panel of each section. Panels shaded in gray are classified as composite and are excluded from the AGN outflow average. Values of v0, W80, and vout are listed for each of the 13 galaxies in Table 2.1.

27 tion 2.4.1, with nine objects hosting AGN on top and four SF galaxies on the bottom.

Each panel shows multicomponent fits to the [O iii] doublet of each galaxy. The spectra have been extracted from within R50 and normalized by the continuum flux just redward of [O iii]λ5007. As in Figs. 2.3 and 2.4, green curves trace the narrow component, orange curves indicate the outflow component, and contaminating Fe I lines are shown in gray. The orange curves in the two bottom right panels represent averages of the fits to AGN and star forming outflows, weighted by the luminosity of each narrow [O iii] component. The composite outflow objects are shaded gray and are not included in the weighted averagefor

AGN.

A comparison of the average AGN vs. star-forming emission line profiles reveals a fundamentally different line shape, with AGN outflows that are blueshifted with respectto the narrow component by ∼100 km s−1, on average. This is in contrast with the outflows in star forming galaxies that show virtually no velocity offset. The broad component of the average AGN driven outflow line profile carries a larger percentage of the total[O iii] flux

than its star forming counterpart (22.8% and 4.9%, respectively).

There is no discernible difference between the stellar masses of the galaxies with

and without outflows. However, the six galaxies with non-AGN driven outflows show signs

of very active star formation relative to the rest of the sample. As we will further discuss in

Section 2.5.4, the galaxies with AGN-driven outflows have redder colors than the four star

forming galaxies and two AGN with stellar driven winds. These six galaxies with non-AGN-

driven outflows have the highest specific star formation rates(log(sSFR Gyr−1) > -0.5 ) of

28 the entire sample of 50 dwarfs. The galaxies with AGN-driven outflows have sSFRs similar to the galaxies with no outflows (-0.5 < log(sSFR Gyr−1) < -3) [74] .

2.4.3 Spatially Resolved Properties of Outflows

Common trends in the behavior of AGN-driven outflows as a function of radius are apparent. In general, the width of the broad component (W80) broadens, the mean velocity offset of the broad component relative to the narrow (v0) approaches zero, and the ratio of the broad to narrow component fluxes (Fb/Fn) increases with increasing radius.

These trends are typical for the AGN in our sample. As an example, we show the spatial properties of the outflow in J090613.75+561015.5 in Fig. 2.7. This object was chosen due

9 to its intermediate mass (2 × 10 M⊙) and color (u − rmodel ∼ 1.7), with respect to the rest of the galaxies hosting AGN driven outflows discussed here. The detailed spatial properties of the remaining galaxies are shown in Appendix A.2.

We confirm that the outflows extend all the way to the limit where our observations have a sufficiently high signal-to-noise ratio to fit[O iii] (between 1.5 and 3 kpc from the center). In addition, their integrated line flux ratios are consistent with AGN out to these distances, indicating that the effect of the central AGN in these dwarfs is largely non-local.

Greene, et al. [130] use spatially resolved longslit spectroscopy of luminous obscured quasars to extend the relation between NLR size and [O iii] luminosity and linewidth by an order of magnitude. To test whether the AGN would be able to ionize gas out to the distances in their host galaxies where we detect signal, we estimate the expected sizes of the narrow line regions (NLR) using this relation. We find that the NLR sizes range between

29 J0906+56 ) 1

− 1700 s

m 1400 k ( 0

8 1100 W 1.5 1.0 0.5 0.0 0.5 1.0 1.5 ) 0 1 −

s 50 m

k 100 ( 0

v 150 101 1.5 1.0 0.5 0.0 0.5 1.0 1.5 n

F 0

/ 10 b F

10-1 1.5 1.0 0.5 0.0 0.5 1.0 1.5 r (kpc)

Figure 2.7: Spatial properties of the AGN-driven outflow in J090613.75+561015.5. The outflow width W80 and offset v0 as defined in Section 2.3.4 as a function of radius areshown in the top two panels, respectively. The ratio of the broad to narrow [O iii] flux is shown in the bottom panel.

30 3.1 and 3.5 kpc, well beyond the distances where we are able to measure line ratios (<3 kpc in all cases).

2.5 Discussion

2.5.1 Ionization by Star Formation vs. AGN

For simplicity, the outflows in this paper are classified as SF, composite, andAGN- driven based on the position of their broad components on the BPT diagram in Fig. 2.5.

We see that the broad outflow components for all four SF galaxies (cyan triangles) fall below and to the right of their corresponding narrow components, likely due to the contribution from shock-induced photoionization [4]. Stellar-driven outflows are commonly observed in massive starburst galaxies [257] and, at least in those galaxies, shocks often propagate through the ISM [291]. Thus, it is likely that the fast outflows in these four star forming galaxies are driven by stellar processes and at least partially ionized by shock heating. Though we cannot positively rule out the presence of faint or extremely variable

AGN, we find no optical or IR evidence of AGN that could be driving the outflows inthese control sample galaxies.

Six objects in our sample have broad components falling on or above the [165] line on the BPT diagram (solid black line in Fig. 2.5), indicating that they exceed the theoretical maximum ionization possible with star formation alone. We consider AGN to be the most likely mechanism for driving the outflows in these objects.

Two AGNs have outflow components that fall in the composite region, indicating a significant contribution from star formation to the ionization of these components. This

31 star formation contribution is more pronounced in the outflowing gas than the bulk of the bound gas (narrow component) in the galaxy. Thus, we regard these two objects as dwarfs that likely contain AGN, but whose outflows might be at least partially powered by star formation.

As mentioned above, we were not able to measure line flux ratios for the broad component of the remaining object, J084025.54+181858.9, due to their lower signal-to-noise ratio.

Note that J100935.66+265648.9 follows a similar trend to the two objects with composite broad components (gray diamonds) in that its broad component falls closer to the composite region of the BPT diagram relative to its narrow component. The inclusion of an additional broad Hα component with FWHM = 298 km s−1 to the Hα + [N ii] model described in Section 2.3.2 was necessary to properly fit the outflow component fluxes for this object. This additional component is too narrow to convincingly be associated with the broad line region, and is possibly tracing an additional kinematic component of the outflow or a velocity gradient along the slit introduced by rotation. Though the broad emission line ratios appear to show significant dilution by star formation, the outflow remains on or above the [165] maximum starburst line. Thus, we count this object among those with

AGN-driven outflows in our sample.

2.5.2 Outflow Line Profiles

Additional evidence of outflow origin could be inferred from the different structure of the spectral lines for AGN vs. star formation powered outflows. The average line profiles of AGN shown in Fig. 2.6 are more blueshifted and slightly less broad than those of SF

32 galaxies. This could be interpreted by considering the physical position of the source of the winds. In any given galaxy with radial outflows, the blueshifted gas will be easier to detect since the gas suffers from less galactic obscuration than the gas moving away from the observer (e.g., [291, 80]).

We speculate that the blueshifted outflow component can be explained by considering obscuration from denser material in the central regions of the galaxy. If there is only one source, and it is positioned in the center of the galaxy (as would be the case for

AGN), most of the gas we observe will be blueshifted. However, if there are multiple sources scattered around the galaxy, with some of them being on the near side of the galaxy, closer to the observer (as would be the case with supernovae and regions of star formation), then we will be more likely to observe both the blue- and redshifted emission.

In Fig. 2.8, we illustrate the difference in AGN-driven outflow line profiles extracted from the center and the outskirts of a galaxy, using J090613.75+561015.5 as an example. The first panel shows the fit to[O iii]λ5007, extracted from the central ∼ 0.4 kpc– note the blueshifted broad component. An extraction ∼ 1.5 kpc from the center reveals a broad component with a smaller velocity offset and a slightly wider profile, consistent with the scenario where obscuration decreases with radius, revealing emission from both approaching and receding material. The typical radial trends of AGN-driven outflow properties introduced in Section 2.4.3 and Fig. 2.7 would be a natural consequence of the proposed model.

33 Figure 2.8: A comparison between outflow component line profiles extracted from the central ∼ 0.4 kpc and ∼ 1.5 kpc from the center of J090613.75+561015.5 is shown. We speculate that the central outflow appears blueshifted due to denser material in the center of thegalaxy obscuring emission from the redshifted gas escaping the far side of the galaxy. Farther from the center, the outflow profile widens and the velocity offset becomes less pronounced as galactic obscuration fades and both blue- and redshifted portions of the outflow is revealed.

34 1200 AGN with outflows AGN with SF outflows 1000 SF with outflows ) 1

− 800 s

m k (

u 600 o v

400

200 200 250 300 350 400 1 vesc (km s− )

Figure 2.9: Relation between the velocity measured for the outflows and the modeled escape velocity assuming galaxies live in massive dark matter halos consistent with the cosmological picture of ΛCDM. In all cases, the wind speed is comparable or above that needed to escape the dark matter halo. To guide the eye, the dashed line indicates a 1-to-1 relation.

35 2.5.3 Gas Velocity

In order to test whether these winds are capable of escaping the gravitational potential of their host halos, we calculated the escape velocity of each galaxy. We assume an NFW dark matter density profile [219] and use abundance matching [212] to estimate the halo mass from stellar mass for each galaxy. The escape velocity is

2 vesc(r) = 2 |Φ(r)| (2.2) where Φ is the gravitational potential corresponding to a spherical NFW profile [190]. The escape velocities for all 13 outflow galaxies were calculated at r = 0 kpc. Calculating escape velocity from the center of a cuspy dark matter halo constitutes an upper limit, as escape velocity decreases with radius. A cored dark matter profile for dwarfs, as has been suggested from observations of some dwarf galaxies [2, 227], will also result on a lower escape speed, facilitating the gas removal. Halo mass predictions and escape velocities for each outflow galaxy are listed in Table 2.1.

Figure 2.9 compares the velocity of the outflow vout to an upper limit of the escape velocity vesc. As discussed in Section 2.3.4, we measure vout in our targets by taking the

velocity blueshift corresponding to the 80% width of the detected broad lines plus the offset

from the system’s velocity (Fig. 2.3). The fit is performed on spectra extracted from within

R50. The length of the horizontal arrows in Fig. 2.9 shows the impact of changing the

assumption of halo concentration from c = 15 to c = 8. The symbol sizes in Figs 2.9 and

2.10 are proportional to the percentage of [O iii] flux in the outflow (i.e. the ratio ofthe

flux of the broad component to the total [O iii] line flux). The velocities plotted in Fig. 2.9

36 as well as the flux ratios that determine the symbol sizes are listed in Table 2.1andthe details of their calculations can be found in Section 2.3.4.

In all cases the outflow velocities surpass vesc, suggesting that the ionized gas entrained in the outflow will become unbound from the galaxy and, later, its dark matter halo.

2.5.4 Feedback

AGN feedback has been studied extensively at higher masses, invoking winds to explain both suppressing [92, 105] and enhancing [91, 114, 153] effects on star formation.

Studies of galaxy evolution placing AGN on the color-mass diagram imply a scenario where

AGN mark a sudden transition from blue, star forming galaxies into quiescent red galaxies

[199]. A large body of theoretical [167, 312, 305] and observational [270, 218, 96] work has been conducted in the high mass regime to investigate whether AGN can regulate star formation by means of expelling gas or by disrupting cooling flows that would otherwise fall in and fuel star formation.

Figure 2.10 shows that dwarfs with detected outflows associated with AGN (pink circles) have intermediate colors that strike between the blue, actively star forming population, and the redder, quiescent population. Their position is at least qualitatively consistent with the evolutionary scenario proposed at higher masses. Non-AGN star forming galaxies with outflows (cyan triangles) are among the bluest in our sample, as is expected fromvery young and active stellar populations. In the bluest AGN hosts discussed here, the outflows

37 3.5

3.0

2.5 l e d o 2.0 m ) r −

u 1.5 (

1.0 AGN with outflows AGN with SF outflows 0.5 SF with outflows no outflows 0.0 8.0 8.5 9.0 9.5 10.0 10.5 11.0 11.5 log10(M /M ) ¯

Figure 2.10: The u − r model magnitude colors from SDSS DR 8 are plotted against the MPA-JHU stellar mass. The colors are corrected for galactic extinction, following [280] and the contours are from [278]. The photometry for NGC 1569 were measured in GALEX [124] and converted to SDSS ugriz via the Python code pysynphot. The outflow symbol sizes are scaled to the fraction of [O iii] flux contained in the outflows.

38 appear to be at least partially powered by coincident stellar processes (gray diamonds).

These galaxies retain their blue colors despite having fast outflows. This could imply that the outflows are not quenching the star formation, or it could be that the timescale for galaxy color evolution is longer than the specific stage of the outflows at which weare capturing these objects.

In a scenario where AGN-driven outflows suppress star formation, one might expect to find such outflows in redder galaxies. An alternative explanation for thistrendis that optically selected AGN are more easily detected in galaxies with lower star formation rates. Though our selection criteria relies exclusively on emission line properties and does not consider photometry at all, contribution to gas ionization from young stellar populations can obscure optical emission line signatures of AGN. Our star forming galaxies lack all available indicators of AGN; however, we cannot definitively rule out the presence of faint AGN activity coincident with active star formation in our control sample.

All of the outflow galaxies discussed here haveα H equivalent widths (EWHα) well above 3 Å, and thus cannot be considered retired (EWHα < 3 Å) or quenched (EWHα <

0.5 Å) [69]. If the presence of outflows does imply removal of all of the gas in the dwarf galaxy, we are likely catching these galaxies in a phase prior to quenching. This is in contrast to other observational work suggesting AGN feedback works to suppress star formation after an initial quenching event, likely due to tidal stripping by a neighboring galaxy [238].

AGN-driven outflows are suspected to play a major role in quenching star formation in the most massive galaxies. The AGN-driven outflow velocities we report in this work are comparable to those measured in some higher mass galaxies (e.g., [140, 258, 15]).

39 If AGN-powered winds are suspected to quench star formation in those high mass galaxies, the similar wind velocities that we measure could be a plausible quenching mechanism in the dwarf regime as well. The ability of these AGN to quench their host galaxies ultimately depends on the fraction of gas mass involved in the outflow. Due to substantial slit losses and unconstrained electron densities, estimates of outflow gas mass using our current data would span many orders of magnitude. Follow-up observations of two of the AGN presented here and a thorough discussion of mass, kinetic energy, and ionization conditions of the outflows will be presented in a follow up paper (W. Liu et al., inprep.)

2.6 Summary

We have presented the detection and kinematic measurements of extended outflows in isolated dwarf galaxies. Our Keck LRIS longslit data provided spatially resolved spectroscopy, in all cases revealing galaxy-wide winds with velocities exceeding the escape velocities of their dark matter halos. Based on emission line ratios of the outflow components, we found the central AGN to be the dominant driving mechanism in at least six of

13 galaxies. We summarize our conclusions below.

1. Thirteen of 50 dwarf galaxies both with and without optical signs of AGN show

galaxy-wide winds. Nine of these 13 galaxies are classified as AGN according to their

narrow line flux ratios. The remaining four have no optical or IR signatures ofAGN

activity and are thus classified as star forming.

2. We were able to measure BPT emission line ratios for the broad components of 12

of the 13 galaxies with outflows. The four galaxies classified as SF based ontheir

40 narrow line ratios have outflow line ratios consistent with SF ionization plus some

contribution from shocks.

Of the nine AGN, two have outflow line ratios that fall in the BPT composite region,

indicating that their outflows might be at least partially powered by star formation.

One AGN had insufficient outflow flux to place it on the BPT diagram. The remaining

six AGN have outflow line ratios that exceed the theoretical maximum ionization

possible with star formation alone. Therefore, we report the detection of AGN driven

outflows in at least six dwarf galaxies.

3. Outflow velocities were measured to be 375−1090 km s−1 for galaxies with and without

8 9 AGN, ranging in stellar mass ∼ 4 × 10 − 9 × 10 M⊙. The outflow velocities in all 13

galaxies are sufficient to escape their dark matter halos.

4. SF galaxies and AGN show differences in the line profiles of their outflow components.

AGN outflow profiles tend to be more blueshifted and slightly narrower than those

of SF galaxies. Outflows with BPT composite line ratios have line profiles similar to

those in SF galaxies. We speculate that the differences may be due to the differing

physical placement of the wind sources for each of these type of objects.

5. AGN-driven outflows tend to carry a larger fraction (5 − 50%) of the total amount of

[O iii] flux than the SF outflows (4 − 8%). The outflows carrying the largest fractions

of ionized gas tend to populate redder galaxies. The placement of the AGN-driven

outflows on the color-mass diagram is suggestive of ongoing star formation suppression

due to the influence of the AGN.

41 The outflow velocities reported here serve as the first directly observed AGN-driven outflows in dwarf galaxies and offer vital observational constraints necessary toextend realistic feedback models into the low mass regime. Detailed observational followup is needed to constrain the gas mass, spatial extent, and energetics of the outflows in these galaxies. Careful consideration of the potential contribution of shock heating to line ratios is also necessary.

Fast outflows exist in a third of the low-mass AGN hosts in our sample of50 dwarfs, so a systematic search for AGN-driven outflows in a much larger parent sample of dwarf galaxies is warranted.

Acknowledgements

We thank the anonymous referee, whose careful reading and constructive suggestions helped improve and clarify this manuscript. Support for this program was provided by the Na- tional Science Foundation, under grant number AST 1817233. Additional support was provided by NASA through a grant from the Space Telescope Science Institute (Program

AR- 14582.001-A), which is operated by the Association of Universities for Research in

Astronomy, Incorporated, under NASA contract NAS5-26555. LVS acknowledges support from the Hellman Foundation. The data presented herein were obtained at the W. M. Keck

Observatory, which is operated as a scientific partnership among the California Institute of

Technology, the University of California and the National Aeronautics and Space Admin- istration. The Observatory was made possible by the generous financial support of the W.

M. Keck Foundation. The authors wish to recognize and acknowledge the very significant cultural role and reverence that the summit of Mauna Kea has always had within the In-

42 digenous Hawaiian community. We are most fortunate to have the opportunity to conduct observations from this mountain. Some of the data presented herein were obtained using the

UCI Remote Observing Facility, made possible by a generous gift from John and Ruth Ann

Evans. This research has made use of the NASA/IPAC Extragalactic Database (NED), which is operated by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.

43 Name z M∗ Mhalo v0 W80 vout vesc Fb/Ftot narrow broad (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) AGN J081145.29+232825.7 0.016 9.02 11.02 −120 ± 11 634 ± 12 437 ± 167 264 ± 29 0.1002 AGN AGN J084025.54+181858.9 0.015 9.28 11.13 149 ± 44 1627 ± 44 665 ± 62 290 ± 33 0.0467 AGN — J084234.51+031930.7 0.028 9.34 11.17 −72 ± 2.5 607 ± 3.5 375 ± 4.3 299 ± 34 0.5060 Comp AGN J090613.75+561015.5 0.045 9.36 11.19 −128 ± 4.4 1147 ± 5.8 701 ± 7.2 303 ± 35 0.3046 AGN AGN J095418.16+471725.1 0.032 9.49 11.24 −79 ± 5.4 1280 ± 7.9 719 ± 9.6 317 ± 37 0.1542 AGN AGN J100551.19+125740.6 0.0093 9.97 11.49 −176 ± 7.6 1154 ± 8.8 753 ± 17 385 ± 46 0.1740 AGN AGN J100935.66+265648.9 0.014 8.77 10.90 −119 ± 9.8 1055 ± 11 646 ± 15 241 ± 26 0.0587 AGN AGN AGN w/SF outflows J010005.94−011059.0 0.050 9.47 11.24 41 ± 11 929 ± 12 423 ± 16 317 ± 37 0.0616 Comp Comp J144252.78+205451.6 0.043 9.08 11.06 −8 ± 23 1201 ± 25 609 ± 34 273 ± 30 0.0765 AGN Comp

44 Star Forming J101440.21+192448.9 0.028 8.75 10.90 24 ± 14 1114 ± 16 533 ± 21 241 ± 26 0.0431 SF SF J130724.63+523715.2 0.026 9.09 11.05 2 ± 22 1442 ± 24 719 ± 33 272 ± 30 0.0452 SF SF J171759.66+332003.8 0.015 9.85 11.42 −11 ± 35 1509 ± 36 765 ± 50 365 ± 44 0.0482 SF SF NGC 1569 2 Mpc 8.56 10.81 23 ± 8.8 2225 ± 9.4 1090 ± 13 222 ± 23 0.0878 SF SF

Table 2.1: Details of fits to spectra extracted within R50 of each galaxy, unless otherwise specified. (1) Full SDSS names of all13 galaxies with extended outflows (2) Redshift (3) Stellar mass reported in the MPA-JHU catalog (4) Halo mass determined via abundance matching using the method described in the text and the stellar mass listed in (2) (5) Mean velocity of the outflow, in km s−1, relative to the center of the narrow component (negative=blueshifted) (6) Width containing 80% of the flux of the −1 − W80 −1 outflow component, in km s . (7) Outflow velocity defined as vout = v0 + 2 , in km s (8) Velocity required to escape the dark matter halo (3) with an NFW profile from r = 0, in km s−1 (9) Fraction of [O iii] flux in the outflow, calculated asthe ratio of the flux in the broad component, Fb, to the total flux in broad + narrow components, Ftot (10,11) Decomposed BPT classifications for the bound and outflowing gas. In order to optimize S/N, these fits were performed on spectra extractedfrom customized apertures for each galaxy. Chapter 3

Gas Kinematics

We present spatially resolved kinematic measurements of stellar and ionized gas

8.5 10 components of dwarf galaxies in the stellar mass range 10 − 10 M⊙, selected from SDSS

DR7 and DR8 and followed-up with Keck/LRIS spectroscopy. We study the potential effects of active galactic nuclei (AGN) on galaxy-wide gas kinematics by comparing rotation curves of 26 galaxies containing AGN, and 19 control galaxies with no optical or infrared signs of

AGN. We find a strong association between AGN activity and disturbed gas kinematics in the host galaxies. While star forming galaxies in this sample tend to have orderly gas discs that co-rotate with the stars, 73% of the AGN have disturbed gas. We find five out of

45 galaxies have gaseous components in counter-rotation with their stars, and all galaxies exhibiting counter-rotation contain AGN. Six out of seven isolated galaxies with disturbed ionized gas host AGN. At least three AGN fall clearly below the stellar-halo mass relation, which could be interpreted as evidence for ongoing star formation suppression. Taken together, these results provide new evidence supporting the ability of AGN to influence gas

45 kinematics and suppress star formation in dwarf galaxies. This further demonstrates the importance of including AGN as a feedback mechanism in galaxy formation models in the low-mass regime.

3.1 Introduction

In the ΛCDM model of structure formation, dark matter halos form from the gravitational collapse of primordial density fluctuations. Within these halos, baryons collapse into a rotating disc with the same angular momentum as the dark matter halo. With sufficient radiative cooling, the gas is able to collapse and form stars, resulting in a co-rotating disc of gas and stars within a dark matter halo with a density profile which can be approximated by a simple formula [219, 220]. On large scales, the ΛCDM model of structure

formation agrees well with observations of massive galaxies and clusters.

However, large discrepancies in the low-mass regime raise doubts about ΛCDM. For

example, there is a large disagreement between the number of small dark matter halos and

observed dwarfs (missing satellite problem, [207, 170]). There is also a conspicuous absence

of observed large satellites compared to predictions (too big to fail problem, [245, 40]).

Finally, rotation profiles of dwarfs show a variety of inner slopes, indicating a diversity of

dark matter halo profiles, many of which are in disagreement with the predicted NFWdark

matter density profile (cusp vs. core problem, [111, 288, 224]). These departures fromthe

ΛCDM model have prompted some to look into warm (e.g. [193]) or self-interacting dark

matter (e.g. [253]). A promising alternative to re-thinking the nature of dark matter is to

investigate the effects of baryonic feedback on star formation.

46 High resolution simulations conclude that baryonic processes can be used to reconcile the observed properties of dwarf galaxies with ΛCDM [350]. Theoretical work commonly

attributes star formation suppression in dwarf galaxies to heating from the UV background

during reionization (e.g. [162]), stellar radiation (e.g. [103]), and supernovae feedback (e.g.

[150]). Indeed, powerful star-formation driven outflows are observed in starbursting dwarf

galaxies [197, 302], and some observational evidence suggests that stellar feedback may

dominate in dwarf galaxies [200].

Stellar feedback is only part of the picture, as the role of AGN feedback in dwarfs

becomes harder to ignore. Evidence of AGN via optical and infrared (IR) indicators has

been detected in hundreds of nearby dwarf galaxies [247, 209, 273, 9, 31]. Kaviraj et al, [164]

report the IR-selected AGN occupation fraction in high mass galaxies to be 1 − 3%, while

8−10 the same criteria yield a 10 − 30% fraction in dwarf galaxies (M∗ ∼ 10 M⊙). Given

that there are several factors that hinder the detection of AGN in dwarfs [275, 58], this

large AGN fraction can be regarded as a lower limit. These studies suggest that AGN are

common and potentially important phenomena in the low mass regime.

Additionally, observational evidence of AGN-driven outflows in dwarf galaxies has

begun to surface [238, 41, 93, 195]. Each of these studies present observations of AGN

coexisting with kinematically disturbed gas. Such disturbances are distinguished by broad-

ened components in their emission line profiles and velocity measurements indicating gas

that is disconnected or even counter-rotating with respect to their stars. For example,

[298] (henceforth S19) use data from Illustris [328, 123] to investigate the origin of star-gas

counter-rotation in dwarf galaxies. By examining the evolutionary history of simulated

47 galaxies with counter-rotating gas, they found that such counter-rotating components require removal of the original gas reservoir and re-accretion of new gas, with misaligned angular momentum. S19 identify two plausible mechanisms for gas removal: stripping from an encounter with a neighboring galaxy, or AGN outflow events.

The role of AGN feedback in galaxy formation and evolution is not well understood in general. The shallow potential wells of dwarf galaxies leave them particularly susceptible to feedback, making them ideal laboratories to study how the energy output of an AGN couples to the gas in the host galaxy. The discovery of AGN-driven outflows in the dwarf regime challenges current conceptions of feedback in dwarf galaxies and raises the question of whether the gas in these outflows permanently escapes the halo. In this paper, we explore the connection between AGN and kinematically disturbed gas and present further evidence of AGN feedback in dwarf galaxies.

−1 −1 Throughout the paper we assume the cosmological model H0 = 71 km s Mpc ,

Ωm = 0.27, and ΩΛ = 0.73.

3.2 Data

Our complete sample contains 50 nearby (z = 0.05) dwarf galaxies (roughly M⋆ <

10 10 M⊙) drawn from the Sloan Digital Sky Survey (SDSS). SDSS is 95% complete to r band magnitude of 22.2, which is well below the magnitude range covered in this sample

(r ≈ 12 − 17). Twenty-nine of the galaxies in our sample are classified as AGN based on

48 ) β 1 H / ] I I I

O 0

[ disturbed & isolated (

g counter rotating o l 2.0 1.5 1.0 0.5 0.0 0.5 log([NII]/Hα)

AGN 10 10 Star Forming

5 AGN 5

Star forming Number of Galaxies 0 0 0.01 0.03 0.05 8.5 9.0 9.5 10.0 10.5 z log(M /M ) ∗ ¯

Figure 3.1: Top: BPT diagnostic for all 50 galaxies in this sample. The dotted line denotes the [163] classification cutoff, and the solid line is the [165] maximum starburst line. Blue circles indicate isolated galaxies with disturbed gas and with no neighbors of comparable mass (i.e. the neighboring galaxy is at least 0.75 times the stellar mass of the dwarf) within 1.5 Mpc (see Section 3.4.4). Galaxies with counter-rotating stellar and gas components are marked as orange triangles. Bottom:Stacked histograms of redshift and stellar mass of the galaxies presented in this paper. Dark gray represents AGN hosts and light gray represents star forming galaxies.

49 J0021+00 θ = 52.44 J0042-10 θ = 49.82 J0100-01 θ = 43.88 J0156-00 θ = 70.21 J0246-00 θ = 42.89

J0300+00 θ = 76.36 NGC_1569 J0755+24 θ = 56.79 J0802+10 θ = 32.14 J0802+20 θ = 74.80

J0811+23 θ = 15.70 J0812+54 θ = 57.48 J0840+18 θ = 35.71 J0842+03 θ = 18.24 J0851+39 θ = 50.41

J0906+56 θ = 22.53 J0911+61 θ = 85.40 J0921+23 θ = 67.04 J0932+31 θ = 50.95 J0948+09 θ = 47.19

J0949+32 θ = 35.57 J0954+47 θ = 33.42 J1002+59 θ = 43.82 J1005+12 θ = 30.99 J1009+26 θ = 41.10

J1014+19 θ = 45.23 J1143+55 θ = 61.24 J1223+58 θ = 46.34 J1304+07 θ = 28.18 J1307+52 θ = 51.67

J1315+22 θ = 45.59 J1343+25 θ = 70.28 J1401+54 θ = 69.54 J1402+09 θ = 30.40 J1405+11 θ = 74.10

J1407+50 θ = 69.24 J1412+10 θ = 25.58 J1442+20 θ = 32.27 J1458+11 θ = 70.11 J1511+23 θ = 65.67

J1546+03 θ = 85.97 J1608+12 θ = 80.19 J1623+39 θ = 68.86 J1623+45 θ = 60.68 J1644+43 θ = 51.80

J1706+33 θ = 85.80 J1717+33 θ = 60.70 J1721+28 θ = 81.47 J1722+28 θ = 76.84 J2320+15 θ = 18.35

Figure 3.2: colour images of all 50 dwarf galaxies in our sample. All images were generated using the SDSS DR12 finding chart tool, with the exception of NGC 1569, which is outside of the SDSS footprint. The NGC 1569 thumbnail (second row, second column) is a PanSTARS z,g band colour image rendered in the Aladin Lite Viewer with a 3’ field of view (∼ 1 kpc on a side). Each SDSS image is scaled to 10 kpc on a side and the placement of the 1 arcsecond-wide slit is shown in light gray.

50 emission line flux ratios that fall above the [163] star forming sequence on the Baldwin,

Phillips & Terlevich (BPT) diagnostic [11] or the presence of detectable He ii emission

[282]. This sample of 29 dwarf galaxies hosting AGN was selected from the parent samples of [247, 209, 273, 225] based on right ascensions that could be observed during our allotted

Keck time. In order to facilitate spatially resolved kinematic measurements, we prioritized spatially extended galaxies and excluded face-on galaxies whenever possible.

To enable comparison between galaxies with and without AGN, we selected a control sample of 21 star forming galaxies from SDSS Data Release 8, based on their absence of optical and infrared (IR) signatures of AGN. The control sample was selected by applying the same stellar mass and redshift cuts used to build the AGN sample, then excluding objects with emission line flux ratios falling above the star forming sequence on the BPT diagram.

We also excluded all potential AGN using the WISE mid-IR color criteria [155, 299] and further excluded all galaxies with detectable He ii emission. The BPT diagnostic diagram and distributions of the redshifts and stellar masses of our full sample are shown in Figure

3.1.

We collected long-slit spectroscopy of 50 galaxies using the Low Resolution Imaging

Spectrometer on the Keck I telescope (LRIS, [226, 50]). Observation dates, conditions, and spectrograph setups for each object are listed in Table 3.1. The DIMM seeing (Full Width at

Half Maximum value of a star observed at zenith, at 5000Å) is listed for each night. The slit position angles (PA) were determined by fitting r−band SDSS photometry using the IRAF ellipse task. By placing the slit along the semi-major axes determined by these ellipse fits,

51 as shown in Figure 3.2, we obtained spatially resolved spectra, presumably perpendicular to the rotation axis of each galaxy.

52 Name in SDSS Observation Date Seeing slit PA red setup exposure time arcsec CCW N s J002145.80+003327.3 2015-12-05 0.59 42.4 B 1200 J004214.99−104415.0 2015-12-04 0.55 26.9 B 1200 J010005.94−011059.0 2015-12-04 0.55 51.2 B 1200 J015645.30-003737.8 2015-12-04 0.55 126 B 1200 J024656.39-003304.8* 2015-12-04 0.55 131.9 B 1200 J030040.20+000113.3 2015-12-04 0.55 28.3 B 2400 NGC 1569* 2015-12-04 0.55 122.5 B 2400 J075538.19+240103.5 2015-12-04 0.55 0 B 2400 J080212.06+103234.1 2015-12-05 0.59 100.7 B 2400 J080228.83+203050.2 2015-12-04 0.55 73.3 B 2400 J081145.29+232825.7 2015-12-04 0.55 0 B 2400 J081256.37+545808.4 2015-12-05 0.59 32.77 B 1200 J084025.54+181858.9 2015-12-04 0.55 101 B 2400 53 J084234.51+031930.7 2015-12-05 0.59 0 B 1200 J085125.81+393541.7 2015-03-24 0.70 -43.96 C 1200 J090613.75+561015.5 2015-12-04 0.55 0 B 2400 J091122.24+615245.2 2015-03-24 0.70 -13 C 2400 J092149.44+233438.7 2015-12-05 0.59 156.3 B 1200 J093251.11+314145.0 2015-03-25 0.58 -94.6 B 1200 J094800.79+095815.4 2015-12-05 0.59 117.8 B 1200 J094941.20+321315.9 2015-12-04 0.55 64 B 1200 J095418.16+471725.1 2015-12-05 0.59 0 B 2400 J100200.96+591508.3 2015-12-04 0.55 148.5 B 1200 J100551.19+125740.6 2015-12-04 0.55 60.1 B 1200 J100935.66+265648.9 2015-12-05 0.59 45.5 B 1200 J101440.21+192448.9 2015-03-25 0.58 -57.58 B 1200 J114343.76+550019.2 2015-03-25 0.58 -117.58 B 1200 J122342.82+581446.2* 2015-03-24 0.70 -106.86 C 1200 J130434.92+075505.0 2017-06-24 1.17 0 B 1200 Name in SDSS Observation Date Seeing slit PA red setup exposure time arcsec CCW N s J130724.63+523715.2 2015-03-25 0.58 74.09 B 2400 J131503.77+223522.7* 2015-03-24 0.70 -144.8 C 1200 J134332.09+253157.7 2015-03-24 0.70 -21.33 C 2400 J140116.03+542507.4 2015-03-25 0.58 81.76 B 1200 J140228.72+091856.4 2017-06-24 1.17 120 B 1200 J140510.39+114616.9 2017-06-25 0.85 12 A 1200 J140735.47+503242.7 2017-06-25 0.85 163 A 2400 J141208.47+102953.8 2017-06-24 1.17 0.0 B 1200 J144252.78+205451.6 2017-06-24 1.17 101 B 1200 J145843.39+113745.4 2017-06-25 0.85 19 A 1200 J151116.53+233421.6 2017-06-25 0.85 165 A 1200 J154603.78+031339.4 2017-06-24 1.17 31 B 1200

54 J160839.57+120038.5 2017-06-25 0.85 174 A 1200 J162307.88+391847.5 2017-06-24 1.17 80 B 1200 J162335.06+454443.6 2017-06-25 0.85 40 A 1200 J164428.48+435904.2 2017-06-24 1.17 82 B 1200 J170639.14+334103.4 2017-06-25 0.85 156 A 1200 J171759.66+332003.8 2017-06-24 1.17 68 B 1200 J172125.92+281134.9 2017-06-24 1.17 168 B 1200 J172208.82+280155.8 2017-06-24 1.17 130 B 1200 J232028.21+150420.9* 2015-12-04 0.55 122.2 B 1200

Table 3.1: LRIS configuration for each object, using the 1”slit placed along the semimajor axis of each galaxy. For the blueside (LRIS-B), we used the 600 groove mm−1 grism blazed at 4000Å, yielding a dispersion of 0.63Å pixel−1. We used three setups on the red side (LRIS-R): A: 600 groove mm−1 grating blazed at 5000Å, 5600Å dichroic, yielding a dispersion of 0.80Å pixel−1 B: 900 groove mm−1 grating blazed at 5500Å, 5600Å dichroic, yielding a dispersion of 0.53Å pixel−1 C: 1200 groove mm−1 grating blazed at 7500Å, 5000Å dichroic, yielding a dispersion of 0.40Å pixel−1 The LRIS data were reduced using a Python pipeline to automate the standard

IRAF reduction tasks. Flexure on the red camera was corrected using the average shift in sky lines. Sky lines are sparse in the wavelength range covered by the blue CCD, so each galaxy spectrum on the blue side was redshift-corrected using the redshift measured from the flexure-corrected red spectrum. Flexure on the blue CCD was then calculated by comparing redshift-corrected galaxy emission lines with their expected rest frame values.

The longslit spectra were rectified along both the wavelength and spatial axes, yielding

2-dimensional spectra where each pixel row along the spatial axis is a fully reduced 1- dimensional spectrum.

3.3 Analysis

3.3.1 Spatially Resolved Spectra

The longslit spectra have been rectified along both the wavelength and spatial axes, creating a 2D spectrum where each pixel row is a fully reduced 1D spectrum. Much of our analysis depends on fitting subtle spectral features, and thus require high signal to noise (S/N), especially in the dim outskirts of each galaxy. To achieve the required S/N, we spatially bin the spectra, using larger bins on the outskirts of the galaxy, as shown in

Figure 3.3.

Spectra were extracted along the slit by summing pixel rows until the target S/N ratio (typically 15−20) or maximum bin size was reached. In order to prevent summing the entire image and losing spatial data, the maximum bin size is set to be 20% of the spatial axis. The signal to noise was measured using the mean and standard deviation of

55 20

10 Signal to noise 5

0 0 50 100 150 200 pixel

Figure 3.3: Pixel number along the spatial axis is shown on the x axis. The y axis shows the signal to noise ratio of a featureless portion of the spectrum red-ward of [O iii]λ5007. Moving along the slit, we summed pixel rows (black) until the integrated spectrum’s signal to noise ratio (green) reached the target S/N (red) or the maximum bin size was reached. The minimum bin size is 3 pixel rows, which sometimes results in even higher S/N. Exposure times for each object were chosen with the intention of obtaining sufficient S/N in the outskirts, so the bin size is dependent on the observational setup used.

a relatively featureless portion of the stellar spectrum, just red-ward of [O iii]λ5007. The

next bin would begin at the central pixel of the last bin. Figure 3.3 shows the signal to

noise of each pixel row along the spatial axis (black). Vertical gray lines mark the divisions

between bins, and the green line indicates the signal to noise when all pixel rows within

each bin is summed.

56 3.3.2 Emission Line Fluxes

In order to measure accurate emission line fluxes, it is necessary to account for stellar absorption, which primarily affects the Balmer emission lines. The Penalized Pixel-

Fitting software (ppxf) [59] is used to fit and subtract the stellar continuum following the method described in [195] (henceforth Paper I), Section 3.1.

After subtracting the best-fitting stellar population model of the galaxy, the residual emission lines were fit using a custom Bayesian MCMC maximum likelihood sampling algorithm, implemented using the Python package emcee [113]. A single-Gaussian model was used to fit emission lines for each galaxy in this sample, except in 13 cases whenasec- ond Gaussian component was needed (Paper I). In these 13 cases the BPT flux ratios of the narrow component of the emission lines are shown in Figure 3.1 and used when classifying these galaxies as AGN or star forming.

3.3.3 Multi-Component Velocity Measurements

In the ppxf software, emission lines are modeled as Gaussians and fit simultaneously with stellar templates. Each stellar and gas template can be matched to a unique kinematic component, enabling the decomposition of multiple distinct line of sight velocities for stars and various species of emission lines. Each spatially resolved velocity measurement presented in this work consists of three components: stellar, ionized hydrogen, and forbidden gas emission.

To avoid systematic errors introduced by wavelength calibration on the blue CCD, we fit ∼ 1000Å sections of the spectrum using ppxf. Due to the strength of the Hβ and

57 [O iii] emission lines, and their proximity to the stellar feature MgIb, we measured line of sight velocities using the spectral region at rest wavelength 4500 − 5560Å whenever

favorable. Five galaxies were observed using the 5000Å dichroic, which disrupts the Hβ,

[O iii] region of the spectrum. In these cases, stellar and gas kinematics were measured by fitting the portion of the spectrum containing [O ii] and Balmer break (3650 − 4550Å).

In cases where the [O iii] lines were faint, the fitting area containing Hα, [N ii], and [S ii]

(6400 − 6800Å) enabled gas velocity measurements to extend to a larger radius than fitting the 4500 − 5560Å region. An example of fits to these three regions is shown in Figure 3.4.

Thirteen galaxies in our sample have gas profiles that cannot be accurately modeled by a single Gaussian. In these cases, two Gaussian components were used for each emission line: a narrow and a broad. The velocity measurements presented in this work were obtained from the narrow Gaussian components.

3.3.4 Circular Velocity Curves

We extracted spatially resolved spectra along the semimajor axis of each galaxy by summing pixel rows, as described in Section 3.3.1. Multicomponent line of sight velocity measurements were then taken from each spectrum following the method outlined in Section

3.3.3. To convert line of sight velocity measured in ppxf into rotational velocity, we correct for the disc inclination angle (see Appendix A.3). Zero velocity is measured at the galaxy’s kinematic center, which is determined by the point of symmetry in the stellar velocity curve.

Figure 3.5 shows the resulting rotational velocity curve for J170639.14+334103.4 as an example. Stellar velocity measurements are plotted as gray stars and the ionized gas

58 Example pPXF fits 7.5 Case 1 [OII] doublet Hζ H² Hδ λ

F 5.0

, x u l

F 2.5

0.0 3700 3800 3900 4000 4100 4200

Case 2 Hβ [OIII] doublet 7.5 λ F

, 5.0 x u l F 2.5

0.0 4700 4800 4900 5000 5100 5200 5300

15 Case 3

λ 10 F

, x

u Hα, [NII] [SII] l

F 5

0 6400 6500 6600 6700 rest wavelength, λ(Å)

Figure 3.4: Example ppxf fits to each of the three spectral sections used to determine velocity curves. Each velocity curve consists of three components: stellar (red), hydrogen (orange), and forbidden (purple, green, and blue).

59 velocities for Hβ and [O iii] are shown as orange and teal circles, respectively. r50 refers to the 50% SDSS r-band Petrosian radius. The gray shaded region shows the analytic prediction of the rotation curve assuming the dark matter halo follows an NFW density profile (see Section 3.4.1).

3.4 Results

We obtained circular velocity curves for the stellar and ionized gas components of all 50 galaxies. Five galaxies are excluded from the rest of this analysis based on the limited spatial extent of their stellar velocity curves. For three galaxies (J024656.39-003304.8,

J131503.77+223522.7, and J232028.21+150420.9), the spatial extent of their velocity curves were comparable (within 0.3 arcsec) with the seeing. NGC 1569 was excluded because the slit only covered the central 0.25 kpc of the galaxy. J122342.82+581446.2 was excluded because we were unable to achieve a sufficient S/N ratio to obtain more than two stellar velocity measurements. Rotation curves for the remaining 45 galaxies (26 AGN and 19 star forming) included in this analysis are shown in Appendix A.4.

3.4.1 Comparison with NFW

The ΛCDM model predicts that dark matter halos will follow an NFW profile, where the density steepens quickly in the inner regions and more slowly in the outer regions, forming a ‘cusp’ profile. However, observed dwarf galaxy rotation curves show a variety of slopes in their velocity profiles, some of which rise linearly with radius [227], implying

60 Rotation Curve Example

150 stars Hbeta 100 [OIII] 50

50 velocity (km/s)

100

150

2 0 2

r/r50

Figure 3.5: The object J170639.14+334103.4 was chosen randomly from our sample to provide an example of an orderly rotation curve, with a co-rotating disc of gas and stars. The stellar (gray stars), Hβ (orange circles) and [O iii] (teal circles) velocities are shown as a function of normalized radius, where r50 is the r-band Petrosian 50% radius. The dotted black line indicates the expected velocity curve for an NFW profile with concentration parameter c = 10. The shaded gray region represents the NFW curve expected from halos with concentration parameter c = 8 − 15.

61 100 AGN, cusp 100 SF, cusp J0021+00 J0921+23 ) 1 − s

m k

( 50 50

t o r v

100 AGN, core SF, core J1405+11 J0812+54 ) 1 − s

m k

( 50

t o r v

0 1 2 3 1 2 3 r/r50 r/r50

Figure 3.6: Four stellar absolute circular velocity curves are shown to demonstrate the variety of inner slopes found in our sample. Two examples of AGN are displayed in the left panels and two star forming galaxies are shown on the right. Dashed black lines and shaded gray regions represent NFW velocity curves corresponding to a halo mass determined by abundance matching, with the MPA-JHU stellar mass as input. Stellar velocity curves showing agreement with the expected NFW profile are shown on the top two panels. The velocity profiles in the bottom panels rise slowly, indicating cored dark matter density profiles.

62 underdense dark matter, or ‘cores,’ in some galactic centers. This diversity in inferred dark matter profiles reported in a large number of observational studies and is yettobe explained by baryonic feedback models (e.g. [272]). Since both AGN and stellar feedback have been shown to move large quantities of gas, and thus would be capable of altering the dark matter distribution of their host galaxies (e.g. [127, 201]), the process of forming cores might be a complex interplay between multiple feedback modes. Any observed association between velocity curve shapes and AGN activity could help disentangle role of AGN in shaping dwarf galaxy dark matter halos.

To aid in visual identification of cores in our sample, we plot the NFW velocity curve of a ΛCDM halo corresponding to the predicted halo mass of each galaxy as gray shaded regions in Figures 3.5, 3.6, and all other velocity curve plots in Appendix A.4.

It is difficult to observationally constrain the halo mass of a galaxy, so onepop- ular approach is to use abundance matching (e.g. [212]). Abundance matching assumes a monotonic relation between stellar and halo mass and matches the cumulative abundance of galaxies on that relation. We used abundance matching to estimate the halo mass corresponding to each galaxy’s stellar mass reported in the MPA-JHU catalogue [44, 163, 314].

The only observational input is the stellar mass M⋆, so the halo mass Mh can be estimated

using abundance matching ([212], Equation 2):

[ ( ) ( ) ]− −β γ 1 M∗ Mh M∗ = Mh 2N + (3.1) M1 M1 with four free parameters: N, the normalization parameter, a characteristic mass M1 and low and high mass slopes β and γ.

63 From these estimated halo masses, we estimate a virial radius ( ) 1/3 3 Mh rv = 0 (3.2) 4 πvρc

0 where v = 200 km/s, and ρc = 277.5M⊙/kpc. Assuming an NFW dark matter density profile, we construct a radial mass distribution ([190], Equation 8):

[ ] cs M(r) = g(c) ln(1 + cs) − M (3.3) 1 + cs h

−1 where c is the concentration parameter, s = r/rv, and g(c) = [ln(1+c)−c/(1+c)] .

We estimate the circular velocity curve from the radial mass distribution using v(r) = √ GM(r)/r. The dotted black line in Figure 3.5 represents the rotation curve expected with an NFW profile with concentration parameter c = 10, and the shaded gray region was calculated assuming a concentration parameter between c = 8, 15.

There is no clear correlation between rotational velocity slopes and AGN activity in our sample. Figure 3.6 shows examples of two AGN and two star forming stellar absolute velocity curves in varying levels of agreement with their predicted NFW profiles. The lack of any association between current AGN activity and central mass deficits could be attributed to a difference in time scales for AGN activity and core formation, or a number ofother proposed factors not related to AGN (e.g. [88]). A solution to the cusp-core dilemma appears to be beyond the scope of this work, and it remains to be seen whether AGN play a role in carving out cores in dwarf galaxies.

64 All Dwarfs 10 2+

0 Isolated SF 10 0.0 0.5 1.0 1.5 2.0 AGN ∆off 5 2+ 0 0.0At least 0.51 neighbor1.0 1.5 2.0 10 2+ ∆off 5

0 0.0 0.5 1.0 1.5 2.0 ∆off

Figure 3.7: We define ∆off to be the weighted absolute average of the velocity offset between stars and gas, divided by the average absolute stellar velocity. This metric is used to quantify the degree of separation between the stellar and forbidden gas component. Based on the bimodal distribution of ∆off in our sample, we consider galaxies ∆off >= 0.75 to have kinematically disturbed gas.

65 Offset Gas Stratified Counter-rotating J1717+33 J0842+03 J0949+32 stellar 100 Hβ )

s [OIII] /

m 0 k (

100 θ = 60.70 θ = 18.24 θ = 35.57 log(M ) = 9.85 ∆ = 1.54 log(M ) = 9.33 ∆ = 2.43 log(M ) = 9.22 ∆ = 5.29 ∗ ∗ ∗ 5 0 5 5 0 5 5 0 5 r/r50 r/r50 r/r50

Figure 3.8: Examples of rotation curves where the gas is disturbed in different ways. In some instances, gas is offset from the stars without showing any clear sign of rotation (left). Some AGN have stratified narrow line components, where the Balmer and forbidden lines are kinematically distinct from one another (center). Five galaxies in our sample have gas and stellar discs rotating separately, and sometimes in opposite directions (right).

3.4.2 Peculiar Gas

The gas in these dwarfs show several distinct indications of non-rotational motion, which could be interpreted as inflows, outflows, or recently accreted gas. To identify disturbed gas kinematics, we designed a metric to quantify the relative offset between the gas and stellar rotation curves. ∆off is the weighted average of the absolute velocity offset between the stellar and gas component, divided by the average absolute stellar velocity.

|∆¯ v| ∆off = (3.4) |v¯∗|

where the weighted average of the absolute velocity offset is

∑ | − | i v∗,i vgas,i wi |∆¯ v| = ∑ (3.5) i wi

66 and the weights are the inverse of the combined errors of each velocity measure-

2 2 − 1 ment, wi = (∆v∗,i + ∆vgas,i) 2

This calculation considers the offset between the stellar and forbidden gas component because the [O ii], [O iii], and [S ii] doublets are less affected by the subtraction of the stellar continuum and absorption than Balmer lines. Faint broad lines associated with the

AGN may also contribute to the line profiles, adding further uncertainty in velocities measured using Balmer emission lines. The forbidden [O ii], [O iii], and [S ii] doublets are not

affected by such absorption or broad line region features and therefore give more accurate

velocity measurements.

Histograms of ∆off are shown in Figure 3.7 and individual ∆off values are reported in the figures for each galaxy in Appendix A.4. The top panel shows ∆off for all 45 galaxies with rotation curves, the middle panel shows the distribution for all isolated galaxies, and the bottom shows the distribution for all galaxies that have at least one neighbor of comparable (or greater) mass (see Section 3.4.4 for a discussion on galaxy environment). The histograms show a bimodal distribution, which is most pronounced in the middle panel.

Based on this bimodality, we classify a galaxy as ‘disturbed’ when ∆off ≥ 0.75 (dotted gray line).

Two galaxies (J010005.94-011059.0 and J090613.75+561015.5) have ∆off < 0.75 between the stars and forbidden emission lines, but the Balmer and forbidden gas components are offset from one another. Following the same approach, we determine the threshold for offset Balmer and forbidden emission components tobe(Hβ - [O iii] ∆off > 0.5). Distinct kinematics associated with higher ionization emission lines is known as line stratification

67 (see Section 3.4.2), and we count galaxies with stratified emission lines among the galaxies with disturbed gas. By this criteria, 25 of the 45 galaxies with rotation curves are disturbed.

All rotation curves are plotted in Appendix A.4. The rotation curves showing orderly, co- rotating discs are shown in Figure A.3 and 25 disturbed rotation curves are shown in Figure

A.4.

Of the 25 galaxies with disturbed gas, 19 host AGN and 6 do not. The majority

(73%) the AGN in our sample have disturbed gas, while only 32% of star forming galaxies have ∆off > 0.75. We noticed distinct properties in the non-rotational motion exhibited in the disturbed gas, and we show examples of rotation curves exhibiting different types of disturbances. We observe gas that is generally offset from the stellar component, stratified emission lines, and counter-rotating gas. Examples of each type of disturbance are shown in Figure 3.8.

Line Stratification

In the stratified model of the narrow line region (NLR), lower ionization gas resides on the outer parts of the NLR while higher ionization lines are generated closer to the AGN

(e.g. [81, 5]). Distinct kinematics associated with emission lines of different ionization potentials imply a complex narrow line region that is stratified in ionization and wind speed.

We observe stratified gas components in seven AGN in our sample, with higher ionization lines showing higher velocities than lower ionization lines. This implies a decelerating outflow: where a high velocity, high ionization wind is generated near the AGN, andwhile the low ionization gas in the outer region of the NLR flows more slowly.

68 200 J0042-10 J0802+20 J0932+31 J0949+32 J1304+07 ) s /

m 0 k (

v θ = 49.82 θ = 74.80 θ = 50.95 θ = 35.57 θ = 28.18 200 log(M ) = 9.44 ∆ = 0.78 log(M ) = 10.55∆ = 1.82 log(M ) = 9.62 ∆ = 4.98 log(M ) = 9.22 ∆ = 5.29 log(M ) = 9.41 ∆ = 1.04 ∗ ∗ ∗ ∗ ∗ 5 0 5 5 0 5 5 0 5 5 0 5 5 0 5 r/r50 r/r50 r/r50 r/r50 r/r50

Figure 3.9: The rotation curves for five galaxies with counter-rotating gas are shown here. The colours are as in Figure 3.8, and the blue dots in the middle panel indicate gas velocities measured from the [SII] doublet.

We observe no correlation between wind speed and AGN luminosity, though the line stratification we observe in these seven galaxies preferentially occurs in galaxies that have outflows indicated by broad [O iii] components. Plots of the stratified gas kinematics in these seven galaxies can be found in the Appendix, Figure A.5.

Counter-Rotating

Of the 45 galaxies with rotation curves, five have counter-rotating gas and stellar components, shown in Figure 3.9. Counter rotating gas and stars have long been explained as the effect of the accretion of gas clouds or small satellites after the formation ofthe stellar disc (e.g. [307, 309, 161]). As mentioned in the introduction, S19 found that counter- rotating gas in dwarf galaxies requires substantial gas removal, either via black hole feedback or environmental effects from fly-by interactions with more massive systems. Interestingly, all five counter-rotating dwarfs in our sample host AGN.

S19 also make several predictions about the present-day properties of counter- rotating dwarfs. In cases where re-accretion of gas is gradual, they find that counter-rotation can be very long lived (up to ∼ 2 Gyr). As a result, S19 predict no significant correla-

69 tion with environment. Three counter-rotating galaxies are isolated (J004214.99-104415.0,

J080228.83+203050.2, J093251.11+314145.0) and two (J094941.20+321315.9, J130434.92

+075505.0) have at least one neighbor with comparable mass.

An event that removes most of the original gas reservoir would quench star formation, making it likely that counter-rotating dwarfs will have older stellar populations and appear redder in colour. All five counter-rotating galaxies discussed here have colours u−r > 2, which is redder than the average for our sample (u − r = 1.83). S19 also find a 30% gas deficit in counter-rotating dwarfs at z = 0, relative to control galaxies at fixed stellar mass.

Though most of the galaxies in our sample lack gas mass estimates, we can turn our attention to the six galaxies with HI masses measured in the ALFALFA survey [41]. Of these six, five are not disturbed and one is counter-rotating (J094941.20+321315.9). The five co-rotating

MHI ∼ − galaxies with HI measurements have a wide range of gas fractions ( M∗ 0.23 7.3), and

MHI ∗ the one counter-rotating has the smallest gas fraction ( M∗ = 0.16). The gas component of J094941.20+321315.9 reaches velocities that exceed the predicted NFW curve, suggesting that this galaxy inhabits a more massive halo than predicted from its stellar mass.

3.4.3 Star Formation Suppression

While abundance matching enables us to infer halo masses based on stellar masses, maximum line of sight velocity measurements can be used to place lower limits on the true halo mass of each galaxy. If the measured lower limit of the halo mass of a galaxy exceeds the halo mass inferred from abundance matching to stellar mass, the galaxy can be said to have a lower star formation rate than expected. Figure 3.10 shows absolute line of

70 12 11 12 11

10.5 10.5

.62 M⋆)=9 log(

12 11 12 11

.22 M⋆)=9 log(

12 12

10.5 10.5

.57 M⋆)=9 log(

Figure 3.10: Absolute line of sight velocity (vlos) measurements that far exceed the expected NFW velocity curves based on their stellar masses indicate overmassive dark matter haloes relative to the measured stellar mass, implying ongoing star formation suppression. Stellar (left), Balmer emission (center) and forbidden emission (right) components are shown for the three galaxies in our sample where this is most apparent. Green curves mark expected NFW velocity curves for galaxies with stellar mass log(M⋆) = 10.5, 11, and 12 and concentration parameter c = 10. Black dotted lines denote the expected NFW velocity curves based on each galaxy’s MPA-JHU stellar mass. All three of these galaxies host AGN, and two have counter-rotating gas components, which lends additional evidence potentially associating AGN with gas depletion and star formation suppression in dwarf galaxies.

71 sight velocity curves for the three galaxies in our sample where this is most apparent. As in previous figures, black dotted lines indicate the NFW curve predicted based oneach galaxy’s stellar mass. Green curves mark the NFW curves associated with stellar masses log(M⋆/M⊙) = 10.5, 11, and 12 and concentration parameter c = 10. The absolute line of sight velocity curves for the stellar (left), hydrogen Balmer emission (middle), and forbidden emission (right) components are shown. Line of sight velocities are plotted here in place of circular velocities to avoid errors introduced when correcting for disc inclination (Appendix

A.3).

The three galaxies shown in Figure 3.10 were selected from our sample using a similar approach to the one used to identify disturbed gas in Section 3.4.2. We calculated the offset between each kinematic componentv ( los) and the predicted NFW curve vNFW:

Σi(vlos,i − vNFW)wlos,i ∆vlos, NFW = (3.6) Σiwlos,i

The distribution of ∆vlos, NFW values for each component revealed three outlying galax-

ies that consistently fell above the threshold ∆vlos, NFW > 0.5: J093251.11+314145.0,

J094941.20+321315.9, and J140116.03+542507.4.

These galaxies have measured velocity curves that far exceed the expected NFW profile, indicating that they inhabit much larger halos than expected based on their stellar masses. Their small stellar masses and red colours (u − r ≥ 2.23) suggest ongoing or recent star formation suppression. It is interesting to note that all three galaxies host AGN, and two have counter-rotating gas, consistent with the scenario where AGN clear a substantial amount of gas from their hosts, limiting star formation.

72 3.4.4 Environment

To distinguish between the effects of environmental and secular processes ongas kinematics, we searched for luminous galaxies in the regions surrounding each dwarf. Fol- lowing the method and criteria employed by [154], we queried the SDSS DR12 and 2MASS

− Redshift survey catalogues for luminous neighbors with MKS < 21.5 mag and SDSS

− − r < 16 mag. The completeness limit of this search is MKS = 21.5 mag at z = 0.02;

9 corresponding to M∗ ∼ 8 × 10 M⊙ [122]. This limit is well below the magnitudes expected for galaxies in the mass range explored in this work, so extending the search to the redshift limit of our sample (z = 0.05) has no effect on completeness. The 2MASS Redshift Survey search revealed matches overlooked in the SDSS search due to missing redshifts, but SDSS optical counterparts existed for all 2MASS matches. We use SDSS DR12 g- and r-band photometry and the mass-magnitude relation of [30] to estimate the masses of neighboring galaxies.

We identify galaxies within 1.5 Mpc and ±1000 km s−1 of each dwarf in this sample

as neighbors. Using the g- and r-band mass-magnitude relation, we estimate the mass of

each neighbor. In order to identify isolated galaxies, we count the number of neighbors

with comparable mass (i.e. stellar mass M⋆,neighbor ≥ 0.75 × M⊙,dwarf) within 1.5 Mpc and

±1000 km s−1. The number of neighbors for each dwarf can be found in Table 3.2.

9 A recent study of 62,258 dwarf (M⋆ < 5 × 10 M⊙) galaxies finds no discernible

difference between the environments of AGN and non-AGN dwarf galaxies, suggesting that

environmental factors may not play a dominant role in triggering AGN [177]. Similarly, we

73 find no statistically significant link between AGN and environment. However, [177] suggest that remnants of past interactions may be reflected in gas kinematics.

The importance of environment in disturbing gas kinematics can be explored by considering the bottom panel of Figure 3.7, which shows the distribution of ∆off for galaxies

with at least one neighbor of comparable (or greater) mass within 1.5 Mpc. Star forming

and AGN-hosting galaxies with neighbors show varying degrees of gas disturbance, further

supporting the notion that environment may not play a dominant role in triggering AGN

activity. The most extreme values of ∆off are associated with AGN, suggesting that AGN

are capable of generating large scale disturbances in their host galaxies’ ISM, though the

presence of AGN-hosting galaxies with undisturbed gas implies this is not always the case.

On the other hand, isolated galaxies show a distinct bimodal distribution, where

star forming galaxies tend to have orderly rotating discs, and disturbed gas is almost always

associated with AGN. Table 3.3 lists the seven disturbed, isolated galaxies, six of which host

AGN. Two of these six isolated AGN have counter rotating gas, and three have outflows

indicated by distinct broadened components in [O iii]λ5007, as in Paper I. To clarify, the outflows in these four galaxies are identified with multicomponent Gaussian fitstothe

[O iii] line profile; disturbed gas is determined here by a velocity offset between thenarrow component of the emission lines from the stellar component.

The single isolated and disturbed star forming galaxy, J101440.21+192448.9, was originally included in our sample based on broad lines in Hα [247], which later faded, likely

due to transient stellar activity [8]. This object is classified as an outflow galaxy in Paper I

based on broadened wings in its [O iii] emission line profile. Follow-up Integral Field Unit

74 (IFU) observations with KCWI revealed that the rotation axis of J101440.21+192448.9 is in fact parallel to the slit position in our LRIS observations (Liu et al., in prep). Since the slit is not aligned with the stellar disc, these velocity measurements do not reflect the true rotational velocity of this galaxy.

Follow-up KCWI observations were obtained for eight objects in this sample (Liu et al., in prep). These IFU observations produce line of sight velocities that agree with our longslit measurements and confirm that in all other cases, the LRIS slit was oriented perpendicular to the rotational axes, as intended. Proper slit orientation for the remainder of the sample should be verified with similar follow-up IFU observations, though the confirmation of correct slit placement in all but one galaxy is encouraging. Since J101440.21+192448.9 is an active star forming galaxy with supernova-driven outflows, it is reasonable to surmise that bright star forming regions could outshine the rest of the disc, confusing the photometric fit used to determine slit placement. This calls into question the slit placement for other galaxies with non-rotational kinematics and signs of active star formation, such as

J171759.66+332003.8.

3.5 Summary

From Keck LRIS longslit spectroscopy, we measured rotational velocity curves of

45 dwarf galaxies. Our sample consists of 26 galaxies with AGN and a control sample of

19 star forming galaxies with no optical or IR evidence of AGN. The rotation curves are

75 Abbreviated Redshift log(M∗) log(MBH) r50 BPT HeII neigh- dist- counter- outflow strat- Name (kpc) bors urbed rotating ified (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) J0021+00 0.0180 9.15 — 0.89 AGN AGN 7 – – – – J0042-10 0.0359 9.44 — 1.34 AGN AGN 5 x x – – J0100-01 0.0515 9.44 — 0.99 Comp. Comp. 5 x – x – J0156-00 0.0450 9.39 — 1.91 SF SF 13 x – – – J0246-00 0.0464 9.35 5.7c 1.34 AGN AGN 37 – – – – J0300+00 0.0095 8.72 — 2.11 SF SF 0 – – – – NGC 1569 −80 km s−1 8.56 — 7.09 SF SF – – – x – J0755+24 0.0290 8.85 — 1.78 SF SF 3 – – – – J0802+10 0.0145 9.60 3.6b 1.29 AGN AGN 3 – – – – J0802+20 0.0286 10.6 — 1.97 Comp. AGN 0 x x – – J0811+23 0.0157 9.06 4.4c 0.58 AGN AGN 2 x – x x J0812+54 0.0086 9.29 — 1.49 SF SF 0 – – – – c

76 J0840+18 0.0149 9.13 4.3 0.94 AGN AGN 2 x – x – J0842+03 0.0289 9.33 — 0.75 Comp. AGN 2 x – x x J0851+39 0.0407 9.28 5.4c 1.70 AGN AGN 2 – – – – J0906+56 0.0465 9.37 5.4c 1.51 AGN AGN 5 x – x – J0911+61 0.0263 8.95 — 2.03 SF SF 7 x – – – J0921+23 0.0281 9.27 — 1.27 SF SF 0 – – – – J0932+31 0.0153 9.62 3.5b 0.58 AGN AGN 0 x x – – J0948+09 0.0103 8.73 4.2b 0.73 Comp. AGN 5 x – – x J0949+32 0.0051 9.22 4.1b 0.58 Comp. AGN 6 x x – – J0954+47 0.0326 9.47 4.9c 1.75 AGN AGN 0 x – x – J1002+59 0.0093 9.60 4.1b 1.12 AGN Comp. 1 x – – x J1005+12 0.0093 9.64 4.8b 0.97 AGN AGN 0 x – x – J1009+26 0.0143 8.75 5.1c 0.62 AGN AGN 0 x – x – J1014+19 0.0284 8.56 — 0.88 SF SF 0 x – x – J1143+55 0.0269 8.92 — 1.03 SF SF 1 – – – – J1223+58 0.0146 9.39 6.1b 1.01 AGN AGN 6 – – – – J1304+07 0.0479 9.41 — 1.13 AGN AGN 16 x x – – Abbreviated Redshift log(M∗) log(MBH) r50 BPT HeII neigh- dist- counter- outflow strat- Name (kpc) bors urbed rotating ified J1307+52 0.0259 9.10 — 1.18 SF SF 2 – – – – J1315+22 0.0226 9.20 — 1.58 SF SF 1 – – – – J1343+25 0.0280 9.19 — 3.09 SF SF 3 – – – – J1401+54 0.0059 9.57 3.2b 0.59 AGN AGN 5 – – – – J1402+09 0.0195 8.83 — 0.79 AGN AGN 26 s – – – J1405+11 0.0178 9.23 — 1.15 AGN AGN 4 – – – – J1407+50 0.0070 8.72 — 0.77 Comp. AGN 8 – – – – J1412+10 0.0324 8.99 — 0.56 AGN AGN 3 x – – – J1442+20 0.0426 8.89 — 0.89 AGN AGN 1 x – x x J1458+11 0.0198 9.91 — 2.40 SF SF 0 – – – – J1511+23 0.0143 9.68 — 1.01 SF SF 0 – – – – J1546+03 0.0132 9.49 — 2.05 SF AGN 3 – – – – J1608+12 0.0166 9.75 — 2.65 SF SF 0 – – – – J1623+39 0.0172 9.22 — 2.68 SF SF 2 x – – – 77 J1623+45 0.0064 9.41 — 0.82 AGN AGN 0 x – – – J1644+43 0.0178 9.53 — 0.86 SF SF 0 – – – – J1706+33 0.0301 9.41 — 1.95 SF SF 7 – – – – J1717+33 0.0151 9.85 — 1.03 SF SF 1 x – x – J1721+28 0.0280 10.0 — 3.49 SF SF 0 – – – – J1722+28 0.0281 9.23 — 1.71 SF SF 3 x – – – J2320+15 0.0130 9.57 3.7b 0.59 AGN AGN 6 – – – –

Table 3.2: (1) * indicates objects excluded from this study. (2) Redshift is calculated by fits to stellar absorption lines in LRIS spectra using ppxf. (3) Stellar mass reported in the MPA-JHU catalogue. (4) b Black hole mass lower limits derived using c 2 Eddington Luminosity arguments (M14) Black hole mass estimated using as MBH ∝ R∆V /G, where ∆V is measured from broad Hα, extrapolating the BLR radius – luminosity relation extends into the low mass regime (R13) (5) SDSS Petrosian radius containing 50% of r-band flux, in kiloparsecs. (6) Classification of dominant ionization source based on Gaussian fitsto emission lines using the process described in Section 3.3.2. The spectra were extracted from the central 1kpc of each galaxy. (7) Same as (6) but for HeII classification (S15) (8) Number of galaxies with comparable mass within 1.5 Mpc. (9) Classified as disturbed (see Section 3.4.2) (10) Gas is clearly rotating and offset from stellar component. (11) Has an outflow identified by an additional broad component in as defined in Paper I. (12) Narrow emission lines are stratified (see Section 3.4.2) name log(M⋆) AGN counter- outflow u−r rotating (Paper I) colour J0802+20 10.6 x x 2.39 J0932+31 9.6 x x 2.23 J0954+47 9.5 x x 2.20 J1005+12 9.6 x x 2.16 J1009+26 8.7 x x 1.91 J1014+19 8.6 x 1.25 J1623+45 9.4 x 2.13

Table 3.3: Seven galaxies in our sample have disturbed gas kinematics and no neighbors of comparable mass within 1.5 Mpc and ±1000 km s−1. Six of them host AGN, two have counter-rotating gas, and four have outflows indicated by broad wings in their [OIII]5007 emission line profiles. u − r colour is based on SDSS cModelMag photometry. decomposed into stellar, Balmer emission, and forbidden emission components. In order to investigate the potential effects of AGN on gas kinematics in this sample, we quantified velocity offsets between stellar and gas components. We summarize our conclusions below.

1. We detect counter-rotating gas in five of 45 galaxies, and AGN are present in all

five cases. A study of the occurrence, properties, and evolutionary history ofcounter-

rotating galaxies in Illustris [298] finds that removal and re-accretion of gas is necessary

for counter-rotating gas discs to form, and that periods of AGN activity are sometimes

associated with large drops in gas mass. We find that the properties of the counter-

rotating dwarfs in our sample agree with present-day properties of counter-rotating

dwarf galaxies predicted from Illustris.

2. We use the weighted average of velocity offsets between stellar spectra and emission

lines to identify disturbed gas kinematics. We find disturbed gas in 25 out of45

galaxies in our sample. Of the 26 AGN in our sample, 19 (or 73%) have disturbed

78 gas. Star forming galaxies tend to have orderly, co-rotating gas discs, with only 32%

showing disturbed gas.

3. At least three galaxies in our sample have line of sight velocities far exceeding those

expected based on their stellar masses. These line of sight velocities constitute a

lower limit estimate of true halo mass, indicating that these galaxies inhabit much

more massive dark matter haloes than expected based on their small stellar masses.

This potential evidence of ongoing star formation suppression is most apparent in

three AGN-hosting galaxies within our sample, two of which have counter-rotating

gas. This suggests that AGN could be associated with gas removal and star formation

suppression in dwarf galaxies. A detailed study of the star formation histories of these

galaxies is warranted.

4. In the absence of environmental influence, kinematically disturbed gas is expected to

be caused by secular processes. Fifteen dwarfs in our sample are isolated, with no

neighboring galaxies of comparable mass within 1.5 Mpc and ±1000 km s−1. Of these,

seven galaxies have disturbed gas. We find that six out of seven isolated galaxies with

disturbed gas host AGN.

Our findings imply that AGN play an important, and perhaps dominant, role in disturbing gas and limiting star formation in dwarf galaxies. This represents additional evidence of the importance of AGN-driven winds in dwarf galaxy evolution and further highlights the importance of including AGN feedback in galaxy formation models. A detailed follow-up IFU study of ionized gas kinematics in a subset of these galaxies is in progress

(Liu et. al., in prep). Multiphase gas kinematic measurements, gas mass measurements,

79 and comparison with simulations run with detailed AGN feedback models are necessary for a full understanding of AGN feedback in dwarf galaxies.

Acknowledgements We would like to thank the anonymous referee, whose careful reading and thoughtful feedback has helped to improve and clarify this manuscript.

Support for this program was provided by the National Science Foundation, under grant number AST 1817233. Additional support was provided by NASA through a grant from the Space Telescope Science Institute (Program AR- 14582.001-A), which is operated by the

Association of Universities for Research in Astronomy, Incorporated, under NASA contract

NAS5-26555. The data presented herein were obtained at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California and the National Aeronautics and Space Administration. The

Observatory was made possible by the generous financial support of the W. M. Keck Foun- dation. The authors wish to recognize and acknowledge the very significant cultural role and reverence that the summit of Mauna Kea has always had within the Indigenous Hawaiian community. We are most fortunate to have the opportunity to conduct observations from this mountain. Some of the data presented herein were obtained using the UCI Remote

Observing Facility, made possible by a generous gift from John and Ruth Ann Evans. This research has made use of the NASA/IPAC Extragalactic Database (NED), which is operated by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.

80 Chapter 4

AGN Impact on Dwarf Galaxy

Stellar Populations

4.1 Introduction

One of the fundamental aims in the study of galaxy evolution is to understand the mechanisms that govern star formation activity. Cold gas collapses inside of molecular clouds to form stars, which then produce and inject metals into the interstellar medium

(ISM). These metals form dust and enrich the the next generation of stars as well as the gas in and around the galaxy.

Historically, dwarf galaxies have been classified according to their morphologies, which is related to their star formation activity [148]: dwarf spheroidal systems have no gas or ongoing star formation, dwarf irregular systems have high star formation rates, and

‘transition’ galaxies exhibit recent star formation but host no massive stars [310]. These

81 categorizations can be useful when examining galaxy morphology but provide little physical insight into the galaxy’s evolutionary history.

Assuming the spectral features of a galaxy contain imprints of the galaxy’s evolution, the decomposition of these features could be used to trace that evolution over time

[332], [77]. A galaxy’s star formation history (SFH) describes the mass-weighted record of stellar formation times, thus providing a comprehensive view of the assembly history of the galaxy. It reveals information about stellar populations that would be difficult to interpret solely based on average values. For example, does the presence of young stars among a more mature population signal a recent rejuvenation of star formation, or are they the final generation to form before star formation shuts down?

Star formation histories of low mass galaxies have already revealed a wealth of information about galaxy formation on small scales. For instance, ultrafaint dwarfs have universally old populations and stunted growth for most of their lives, which supports the notion that they were quenched by reionization (e.g. [48]). By contrast, the SFHs of more massive dwarf galaxies appear to depend on environment. All but the most massive satellites of the Milky Way and M31 have ceased star formation, yet isolated dwarfs are nearly always star forming [122], [115]. Yet, the existence of quenched, isolated dwarf galaxies [154] and the lack of dependence of satellite star formation shut-off times and distance to the host [347] indicate that the processes regulating star formation in dwarfs are still not fully understood.

Perhaps AGN activity can account for some of the observed diversity in dwarf galaxy SFHs.

The same spectral fitting methods used to probe star formation histories can also produce chemical evolution histories. Each star retains the metal content of the gas at the

82 time of its formation, so absorption features from metals in stellar atmospheres reveal the average metal-to-hydrogen ratio of the ISM at the time of formation, providing insight into the early epochs of chemical enrichment. Stellar metallicity has been found to correlate with mass, with high mass galaxies exhibiting higher metal content than low mass galaxies

[116], [229]. This scaling relation could place important constraints on galaxy formation and chemical evolution models, but the physical processes governing growth and chemical evolution are still an active area of study. It is thought that low mass galaxies may efficiently remove metal enriched gas from their shallow potential wells, preventing the accumulation of metals in their gas reservoirs. Alternatively, metal-poor gas inflows may dilute existing metals, decreasing the metal-to-hydrogen ratio in the stars born from this gas [84], [86]. Yet another possibility is that star formation efficiency is mass dependant, and that higher mass galaxies are more efficient at converting their gas into stars, boosting metal abundance [45],

[51].

So far, this project has focused on the movement of gas within dwarf galaxies, drawing the conclusion that AGN play a significant role in driving winds. Ultimately, we are interested in understanding whether AGN feedback can explain inefficient star formation in dwarfs. In this chapter, I study the stellar properties of our sample and investigate the relationship between AGN and the many observable properties of the stars in their host galaxies.

83 4.2 Data and Analysis

In this chapter, we further analyze the sample introduced in Chapters 2 and 3.

The longslit data for 50 dwarf galaxies were collected from the Low Resolution Imaging

Spectrometer (LRIS) on Keck I, and were reduced using standard IRAF tasks. For a discussion of sample selection and data reduction, see Section 2 of Chapter 2. For details about the observations, please consult Section 2 of Chapter 3. An example of a fully reduced

2D spectrum is shown in the top panels of Figure 4.1. Each pixel row is a fully reduced

1D spectrum, and customized extractions along the slit are obtained by summing pixel rows. The cyan highlights in the top panels of Figure 4.1 indicate the regions integrated to produce the spectra shown in the middle panels. In this chapter, I refer to the integrated properties of dwarf galaxies, meaning the entire profile of the galaxy is integrated as a single spectrum and fit using the following method.

4.2.1 Star Formation History

I used the Penalized Pixel Fitting software (ppxf) [59] to fit a linear combination

of single-stellar population (SSP) model spectra from the Miles Library of Stellar Spectra

([271]; [106]). A total of 144 spectra form a rectangular grid that spans the age range of

0.06−12.6 Gyr and metallicity [Z/H] = −1.71−0.2, which are then fit to our LRIS spectra using a maximum penalized likelihood approach.

The age-metallicity parameter space is constructed by decomposing each parameter into single bursts of star formation. Each SF burst produces a single stellar population, born at the same from the same gas with the same metal abundance. A Salpeter initial

84 S/N = 29.93

Relative Flux 0 3750 4000 4250 4500 4750 5000 5250 5500 Observed Wavelength (Å) 1e16 1.2 0 1.0 0.8 0.6 1 [M/H] 0.4 0.2 0.0 0.0 0.2 0.4 0.6 0.8 1.0 1.2 log10 Age (Gyr) 1.0

0.5

0.0 0 2 4 6 8 10 12 14

cumulative mass fraction Gyr

Figure 4.1: The ppxf fit to the integrated spectrum of a galaxy is shown. The fully reduced 2D spectrum is shown in the top panel, with the integrated region highlighted in cyan. The middle panel displays the spectra integrated within the highlighted cyan region (black), superimposed with the best fit stellar (red) and gas (blue) model. Fit residuals are plotted in green. The third panel shows the ppxf solution for across stellar age and metallicity intervals. The regularized map shows the mass fraction of stars falling within each interval, with higher mass fractions in yellow. The bottom panel plots the stellar mass fraction over time, which traces the assembly history of the galaxy.

85 mass function (IMF) is assumed when building the library of synthesized SSP spectra, each of which represents a stellar population with a single specified mass, age, and metal abundance. The SSP template spectra are then combined to reproduce the shape and absorption features in the observed spectra by assigning weights to each template. If each

SSP is born from a SF burst of equal mass, the weights will represent the mass fraction of each population.

Inferring the SFH from integrated galaxy light is an ill-posed problem that can result in degeneracies. This can be addressed via linear regularization, using the ‘REGUL’ parameter in ppxf. This parameter imposes a smoothness constraint on the solution, defin- ing the weights assigned to each model spectrum in the age-metallicity grid, and ensuring that the weights of adjacent models in the grid vary smoothly. The grid contains one SSP model spectrum per unit mass, meaning the fitted weights represent relative mass contributions of each population. When integrated along the metallicity axis, the relative mass to light ratios for each population reveal the stellar mass contribution as a function of age, or the stellar mass assembly history of the galaxy.

The integrated spectrum of each galaxy was fit using the SSP model grid described above, along with an order 2 multiplicative polynomial to account for the AGN continuum and Gaussian templates for all strong Ne, O, and H emission lines in the rest wavelength range 3700 − 5560. Hydrogen Balmer emission lines were modeled as a single template, enabling a simultaneous fit for dust reddening using the ‘gas_reddening’ parameter, which assumes a Calzetti extinction curve [52].

86 The results of this non-parametric approach should be interpreted with care, as the results depend on the stellar template libraries chosen and the propagation of other variables included in the fit (e.g. [126],[68]). For this reason, I reduce the number offree parameters in the fit by performing a preliminary fit to each spectrum to determine the stellar kinematics. I then perform a second fit with stellar kinematics fixed in order to extract the SFH. Another limitation to this method is that it relies on the assumption that the SSP templates are eigenvectors, when in reality, they are not. However, this limitation is unavoidable in all existing techniques for estimating SFH.

4.2.2 Mass Weighted Stellar Ages and Abundances

The mass weighted age and metallicity are derived from the SFHs discussed in the previous section, and are given by Equations 1 and 2 in [203]: ∑ wi∑log(tSSP,i) log(AgeSFH) = (4.1) wi

∑ wi∑[Z/H]SSP,i [Z/H]SFH = (4.2) wi

where wi are the weights of the ith template of age tSSP and metallicity [Z/H]SSP,i.

By analyzing ppxf fits to mock spectra, [121] find that the bias and scatter (P ) in these mass-weighted quantities depend heavily on the signal to noise (SN) of the spectrum

k P = p (4.3) SN

87 where kp at various SSP ages can be found in Table 1 of [121]. This value was added in quadrature with the fit errors when reporting uncertainties in mass weighted average quantities.

4.3 Results and Discussion

In previous chapters, SDSS photometry provided rough approximations of the star formation activity in this sample of dwarf galaxies. We found some intriguing associations between AGN-driven gas disturbances and red galaxy colors, which is suggestive of AGN- induced star formation suppression in some galaxies in our sample. In this section, I present a more robust analysis of the stellar populations in isolated galaxies with AGN, galaxies with counter-rotating gas, and galaxies with outflows.

The results of this analysis is summarized in Figure 4.2. The top row of Figure 4.2 shows star formation histories of three groups of galaxies which are potentially affected by

AGN feedback. Cumulative mass fractions trace the stellar mass assembly of each galaxy over time, providing insight into the mechanisms driving their evolution.

A simple way to approach the analysis of global stellar properties is to classify galaxies as ‘blue and active’ or ‘red and passive’ based on a dividing line in (U −B)AB colors

[237]. This approach is simplistic, but it enables the comparison between the galaxies in this sample to the active and passive mass-metallicity relations for local galaxies shown in the bottom row of Figure 4.2 [236]. The divergence of the passive (red) and star forming (blue)

11 relations in galaxies below M⋆ ∼ 10 M⊙ supports the notion that low mass galaxies often

quench by a process known as strangulation. In this scenario, the quenching mechanism

88 z z z 0.1 0.2 0.5 1 2 0.1 0.2 0.5 1 2 0.1 0.2 0.5 1 2 1.0 Isolated AGN Counter-Rotating Outflows

0.8

0.6

0.4

0.2 composite cumulative mass fraction AGN w/neighbors satellite CR SF 0.0 isolated AGN isolated CR AGN 0 5 10 0 5 10 0 5 10 lookback time (Gyr) lookback time (Gyr) lookback time (Gyr)

0.2 Isolated AGN Counter-Rotating Outflows 0.0 J0802+20 J0802+20

0.2 J0932+31 J0932+31 ) ¯ J0842+03 Z J0949+32J0042-10

/ 0.4 J1623+45 J1304+07 Z J1005+12 J1014+19 J1005+12 ( 0.6 J0840+18 g o l J0811+23

0.8 J1009+26 J0954+47 J1009+26 J0954+47 J0100-01 J1307+52 AGN outflow 1.0 isolated J1442+20 J0906+56 AGN with SF outflow satellite SF outflow 1.2 9 10 11 9 10 11 9 10 11 log(M /M ) log(M /M ) log(M /M ) ¯ ¯ ¯

Figure 4.2: Top: The stellar mass growth is traced by the cumulative stellar mass fraction over time. SFHs of all galaxies in the sample are shown as faint gray lines and various groups of interest are highlighted in each panel. Top left: The red lines represent the SFHs of six isolated galaxies with AGN. The AGN galaxies with neighbors are indicated by brown lines and the SFHs for the star forming control sample are shown as faint gray lines. Top middle: The five galaxies in our sample with counter-rotating gas are emphasized. 11 SFHs of counter-rotating galaxies that are satellites of massive (M⋆ > 10 M⊙) galaxies are shown as purple dotted lines, while isolated counter-rotating galaxy SFHs are plotted in solid orange. Top right: Galaxies with outflows detected via broadened [O iii] components are emphasized. SFHs for galaxies with AGN-driven (pink), star formation-driven (blue), and AGN hosting galaxies with star formation-driven outflows (composite; gray) are shown. Bottom: The stellar mass - metallicity relation for active (blue) and passive (red) galaxies is plotted [236]. In each bottom panel, the integrated stellar metal abundances of the galaxies shown in the corresponding top panel are plotted according to the same color schemes.

89 removes some gas from the galaxy while preventing accretion of new gas. The remaining gas is left to form stars, which depletes the gas reservoir while building up the stellar metal abundance.

4.3.1 Are AGN suppressing star formation in isolated galaxies?

Without the effects of interactions with neighboring galaxies, star formation histories are expected to be governed by secular processes. In Chapter 3, we found that isolated galaxies without AGN tend to have orderly gas disks that co-rotate with their stars, while all six isolated galaxies with AGN have disturbed gas kinematics and redder colors.

In this work, SSP fits reveal that the stellar populations in isolated AGN hosts are on average 1.8 Gyr older than the rest of the AGN in the sample. The top left panel of Figure 4.2 shows the star formation histories of the six isolated AGN (red) compared to AGN host galaxies with neighbors (brown). While AGN in more crowded environments display a wide variety of star formation histories, these six isolated galaxies either grow gradually over time or formed 90% of their stars by z = 0.5.

All six isolated galaxies have (U − B)AB colors that place them in the ‘red passive’ category, according to the simplistic color criteria used to differentiate between active and passive mass-metallicity relations in Figure 4.2 [237]. Since our sample selection depends on emission lines, all of the galaxies discussed in this work have detectable ionized gas and thus cannot be considered completely quenched. However, three of these galaxies (J095418.16+471725.1, J100551.19+125740.6 , J100935.66+265648.9; solid red lines) are shedding their gas via AGN-driven outflows, as described in Chapter 2. The rest

(J080228.83+203050.2, J093251.11+314145.0, J162335.06+454443.6; dashed red lines) show

90 Figure 4.3: The full mass weighted stellar age - stellar metallicity grids for all five counter- rotating galaxies are shown, in order of increasing mass. The three galaxies in the top row are satellites and the two in the bottom are isolated. Each block in the grid is associated with a SSP with the specified stellar age and metallicity. The color scheme represents the mass fraction associated with each SSP, where yellow indicates the largest fraction.

signs of suppressed star formation: they all have formed 90% of their stellar mass by z ∼ 0.2 and have small Hα equivalent widths (WHα < 6Å). Furthermore, J093251.11+314145.0 has a lower stellar mass than expected based on its rotational velocity, indicating that the star formation within its massive dark matter halo was suppressed (see Chapter 3, Section 3.4.3).

In short, all of the isolated AGN hosts in this sample appear to be passive and gas depleted, or are actively ejecting gas.

4.3.2 The story behind counter-rotation

In order to form a counter-rotating gas disk, it is thought that a galaxy must first clear its existing co-rotating gas. The mechanism for removing co-rotating gas is not fully understood, but a study of low mass counter-rotating gas in Illustris suggests that large

91 scale outflows or ram pressure stripping from a central galaxy are likely culprits [298].In

Chapter 3, we identified five galaxies with counter-rotating gas. Not only were they much more common than expected, but all of them host AGN. This evidence associates AGN with gas-star counter-rotation, suggesting that AGN may be responsible for clearing these galaxies of their gas. In this section, I examine the average stellar properties and star formation histories of these five galaxies for clues as to how their counter-rotating gas disks came to be.

Since ram pressure stripping by central galaxies is a likely gas removal mechanism, it makes sense to consider galaxy environment when analyzing the SFHs of these five galaxies. Two of the counter-rotating galaxies are isolated and the other three live in rather busy environments. In this section, I refer to these three galaxies as satellites because are all

11 within 0.6 Mpc of a galaxy with mass M⋆ > 10 M⊙.

The SFHs for the satellite and isolated galaxies with counter-rotating gas are shown in the top middle panel of Figure 4.2. The sample is very small, but there is a clear distinction between the SFHs of the isolated and satellite galaxies. The isolated galaxies grew quickly before z = 0.5 and have very little recent star formation, having essentially reached their present day mass by z = 0.2. On the other hand, the satellites appear to experience a late burst of star formation, obtaining roughly 40% of their mass after z = 0.2.

This burst sometimes occurs after a period of relatively slow growth. The five counter- rotating galaxies also have consistently high stellar metal abundances relative to the rest of the AGN in the sample.

92 With only five galaxies, it is difficult to pinpoint a single process responsible for clearing gas to make way for counter-rotating gas. The presence of AGN in all instances of counter-rotating gas is conspicuous, but a larger sample is needed to fully understand the role of AGN in this narrative. The metal rich stellar populations of these counter- rotating galaxies could indicate that the gas removal mechanism at work has also prevented the infall of new gas for a large portion of these galaxies’ lifetimes, stunting their growth through strangulation.

It is unclear from the mass weighted average stellar abundance how these galaxies accumulated their metals. The chemical evolution of these galaxies can best be understood by examining the full age-metal grids of each galaxy, shown in order of increasing mass in

Figure 4.3. The three galaxies on top are satellites and the two on the bottom are isolated.

The satellite galaxies appear to grow the first 20−40% of their mass in a starburst fueled by gas of varying metallicity. J004214.99-104415.0 and J130434.92+075505.0 then experience a period of little to no growth. Then, they have a late burst of star formation, presumably associated with the recently accreted counter-rotating gas. It is interesting to note that the most recent bursts of SF form from enriched gas. On the other hand, isolated counter- rotating galaxies show no signs of recent star formation bursts associated with their accreted gas.

These different evolutionary tracks are difficult to explain solely with themea- surements presented here, but one could hypothesize that the source of counter-rotating gas differs with environment. Perhaps the counter-rotating disks in the satellite galaxies are the results of minor mergers with gas rich, star forming dwarfs. It could be that the

93 young stars observed in the satellite galaxies are formed ex-situ and then accreted along with the gas, rather than formed as a result of cold gas accretion. Meanwhile, the isolated galaxies may have obtained a small amount of non-star forming gas through less dramatic accretion events. Further investigation into this thought could be conducted by decomposing the stellar kinematics by age and searching for a counter-rotating disk of young stars alongside the gas.

4.3.3 Stellar Activity and Outflows

In Chapter 2, we found that the u − r colors of the 13 galaxies with outflows agree

qualitatively with a scenario where AGN-driven outflows mark a transition from blue and

star forming to red and quiescent, as is postulated at higher masses ([270], [218], [167], [96],

[305], [312]). Here, I investigate whether a more detailed analysis of their SFHs will tell the

same story.

In the top right panel of Figure 4.2, we see that galaxies with AGN-driven outflows

(pink) have a variety of SFHs, but in general, they have earlier formation times and are

growing more slowly at z = 0 compared to the other galaxies in the outflow sample. By

contrast, star forming galaxies with outflows (blue) assemble later on average than the rest

of the sample. The two composite galaxies (gray), which host AGN but have outflows that

are likely driven by star formation, are among the fastest growing galaxies in the sample.

In Chapter 2 we speculated that the emission line profiles could hold clues as

to the placement of the source in the galaxy, where blueshifted wings are associated with

centrally located outflow sources while outflow sources scattered throughout the galaxy

would produce symmetrical line profiles (See Chapter 2, Section 5.2 for a more detailed

94 discussion). The outflows in the composite galaxies are thought to be powered bystar formation based on the symmetry of their emission line profiles.

The SFHs measured here support the narrative implied by the u − r photometry.

The seven galaxies with intermediate colors tend to have older stellar populations and earlier

formation times, while the six bluest galaxies have more recent star formation bursts. This

further supports the scenario where star formation driven outflows are found in actively

star forming galaxies, while AGN-driven outflows are associated with a galaxy’s transition

from the blue cloud to the red sequence. The confirmation of rapid stellar mass growth

in the composite galaxies further supports the conclusion that their outflows are driven by

stellar processes, and lends credence to the idea that the positions of outflow sources can

be inferred from their emission line profiles.

4.4 Summary

In this chapter, I used mass-weighted SSP fits to recover star formation and chem-

ical evolution histories for 50 dwarf galaxies. I investigated the integrated properties of

various subgroups of the sample to further understand the role that AGN play in governing

star formation in dwarf galaxies. My results can be summarized as follows:

1. All isolated galaxies with AGN have colors consistent with passive evolution [237] and

either show signs of gas depletion [69] or are in the process of losing their gas[195].

By contrast, isolated galaxies without AGN are all actively star forming, indicating

that when only secular processes are involved, AGN are strongly associated with star

formation suppression.

95 2. Though AGN appear to play a role in removing gas to make way for counter-rotating

disks, environment appears to play a role in the re-accretion of new material. Isolated

counter-rotating galaxies grow gradually from high metallicity gas, forming 80% of

their stellar mass before z = 0.5. Satellite counter-rotating galaxies form from gas

with varying levels of metal enrichment and then grow slowly before experiencing

an apparent burst of star formation fueled by high metallicity gas. Isolated galaxies

with counter-rotating gas do not have a new burst of star formation associated with

new gas accretion. This implies that counter-rotation in isolated galaxies results from

accretion of small amounts of non-star forming gas, while counter-rotating gas in

satellites may originate from mergers with gas rich, star forming dwarfs.

3. Galaxies with AGN-driven outflows have diverse star formation histories, but have

consistently older stellar populations and slower present-day stellar mass growth than

those with star formation-driven outflows. In this chapter, I confirm that the compos-

ite galaxies, which host AGN yet have outflows likely associated with stellar processes,

are indeed undergoing a current burst of star formation. This supports the idea that

emission line profiles may be used in conjunction with flux ratio diagnostics todistin-

guish between AGN and SF driven outflows.

In this chapter, the mass-weighted stellar properties were used to further probe the effects of AGN on the growth of dwarf galaxies. Luminosity-weighted stellar properties are more sensitive to the contributions of younger stellar populations, and could be used to investigate the dominant radiative processes at work in these galaxies. Careful decompositon

96 of stellar spectra to obtain distinct rotation curves for various populations of stars could also lend insight into the merger histories in the counter-rotating dwarfs.

This analysis could also be extended by examining the evolution of individual elements to explore the processes that enrich the ISM. A spatially resolved study of the gas phase metal abundances would also reveal the present day metal content and transport in these dwarfs.

97 name log(M⋆/M⊙) age (Gyr) t50(Gyr) log(Z⋆/Z⊙) J0021+00 9.146986 7.551983 10.520711 -0.589740 J0042-10 9.442602 3.937794 7.683454 -0.364481 J0100-01 9.441348 2.064401 3.268963 -0.856955 J0156-00 9.390523 3.411646 3.292840 -0.638414 J0246-00 9.348598 8.198474 10.681655 -0.366976 J0300+00 8.723645 5.818258 3.837403 -0.626042 NGC 1569 8.560000 3.435674 12.589300 -1.434657 J0755+24 8.851282 3.384052 4.634967 -1.177595 J0802+10 9.600313 8.641875 10.204633 -0.306619 J0802+20 10.553940 6.903988 8.945402 -0.078855 J0811+23 9.060884 7.623616 10.785976 -0.702861 J0812+54 9.285977 5.847416 4.283185 -1.188364 J0840+18 9.133316 8.338386 10.911056 -0.603908 J0842+03 9.330553 4.918787 6.084814 -0.349859 J0851+39 9.277671 1.509083 2.004934 -0.061930 J0906+56 9.372400 5.780641 5.042306 -1.039935 J0911+61 8.946604 1.148056 1.293918 -0.935850 J0921+23 9.268008 4.605948 4.533198 -0.625387 J0932+31 9.620956 8.875524 10.483105 -0.204271 J0948+09 8.730108 9.094378 9.437261 -0.981134 J0949+32 9.220258 6.758339 7.614780 -0.383914 J0954+47 9.466668 9.637536 10.327185 -0.805574 J1002+59 9.600677 7.265508 9.952643 -0.356012 J1005+12 9.635745 5.558454 8.711172 -0.541482 J1009+26 8.749137 5.128555 4.541501 -0.813839 J1014+19 8.563872 4.136424 3.777498 -0.537318 J1143+55 8.924566 3.488165 3.014142 -0.840875 J1223+58 9.392751 9.961965 12.250991 -0.561278 J1304+07 9.410233 4.070558 9.777599 -0.518040 J1307+52 9.096391 3.507890 2.929054 -0.945953 J1315+22 9.197057 5.576337 10.359664 -0.368915 J1343+25 9.185787 9.593189 11.428664 -0.941250 J1401+54 9.567201 8.956039 10.771114 -0.178446 J1402+09 8.832737 7.089637 10.061051 -0.839742 J1405+11 9.226830 4.997284 7.151002 -0.627191 J1407+50 8.721412 8.298145 9.672636 -0.730818 J1412+10 8.992185 3.002057 4.201882 -0.003611 J1442+20 8.891579 2.786269 3.818201 -0.988093 J1458+11 9.908138 6.723958 10.005804 -0.404059 J1511+23 9.684150 4.649176 8.821941 -0.748695 J1546+03 9.487150 3.050479 2.193108 -0.476559

98 name log(M⋆/M⊙) age (Gyr) t50(Gyr) log(Z⋆/Z⊙) J1608+12 9.753928 5.432191 9.280954 -0.762544 J1623+39 9.218903 6.269718 9.995369 -1.075628 J1623+45 9.409533 8.847325 10.927397 -0.480009 J1644+43 9.528967 2.862352 3.227272 -0.959610 J1706+33 9.408504 5.647809 8.791064 -0.989041 J1717+33 9.847754 5.120873 6.050567 -1.346557 J1721+28 10.033380 2.596349 2.150411 -0.307855 J1722+28 9.245996 4.494351 5.481613 -0.763320 J2320+15 9.574848 9.024725 10.878865 -0.194280

Table 4.1: The average integrated mass-weighted stellar age, metal abundance, and formation times for all 50 galaxies.

99 Chapter 5

Summary and Conclusions

It is thought that AGN feedback is the primary mechanism limiting the growth of massive galaxies, while stellar feedback is often invoked to explain star formation suppression in dwarf galaxies. The general conclusion of this work is that AGN activity often has dramatic effects on the gas kinematics of dwarf galaxies, possibly regulating their star formation histories. AGN appear to be important, if not dominant, sources of feedback in the low mass regime and therefore should not be overlooked when investigating dwarf galaxy evolution. Finer points are discussed below:

5.1 AGN are able to expel gas from dwarf galaxies

Broadened wings in the emission line profiles of ionized gas reveal the complex kinematics of a galaxy’s gas. In Chapter 1, we decomposed strong emission line profiles in order to better understand the motion of ionized gas in galaxies with and without signs of AGN. Thirteen out of 50 galaxies contained spatially extended broadened components,

100 tracing a portion of gas moving at higher velocities than the rest of the gas in the galaxy.

By fitting multiple Gaussian components to spatially resolved emission lines, we found that all 13 galaxies showed gas velocities sufficient to escape their dark matter halos.

Of these 13 galaxies with outflowing gas, we identified six galaxies with broadened emission line ratios consistent with ionization from AGN. The emission line profiles of these six galaxies differed from the rest in that their broadened wings were blueshifted near the galactic centers, while the rest had symmetrical emission line profiles. We surmised that attenuation from dust would obscure emission from redshifted material escaping from a centrally located source, resulting in emission line profiles with blueshifted wings. On the other hand, outflow sources scattered throughout the galaxy are less affected bydust attenuation and thus yield symmetrical line profiles.

This work presented the first direct kinemetic measurement of AGN-driven outflows in the low mass regime, and demonstrated that AGN can drive winds capableof escaping dwarf galaxy dark matter halos.

5.2 AGN can affect global gas kinematics

In Chapter 2, we find a strong association between AGN and disturbed gas. In the absence of neighboring galaxies, gas disturbances are expected to be caused by secular processes. We compare the velocities of the gaseous and stellar component in each galaxy and find that all isolated galaxies with AGN have disturbed gas kinematics. By contrast, isolated galaxies without AGN tend to have orderly gaseous disks that co-rotate with the stellar component.

101 We also find gas in counter-rotation with the stars in five galaxies in our sample, all of which host AGN. In order for counter-rotation to occur, it is thought that a galaxy first must shed its original gas, either by large outflow events or by ram pressure stripping, and then accrete new gas with different angular momentum from the stars. The strong association between AGN and counter-rotating gas suggests that AGN are the dominant mechanism for gas removal.

5.3 AGN with disturbed gas are associated with star forma-

tion suppression

The early work in this project found evidence suggestive of AGN- induced star formation suppression in dwarf galaxies. All six galaxies with AGN-driven outflows have intermediate colors that strike between the blue cloud and the red sequence on the color- mass diagram. This is consistent with a scenario where AGN activity marks a galaxy’s transition from blue and star forming to red and passive. Similarly, galaxies with counter- rotating gas tend to have redder colors than the rest of the sample, which is expected if the dwarfs lost their entire gas reservoir before accreting new gas. Furthermore, three galaxies in our sample, all hosting AGN, have maximum rotation velocities indicating they inhabit much more massive dark matter halos than expected from their stellar masses.

These results warrant a detailed investigation into the stellar properties of the dwarf galaxy sample. In Chapter 3, I used SSP modeling to retrieve star formation histories for each galaxy in the sample, to investigate the potential effects of AGN feedback on stellar populations. I found that all isolated galaxies with AGN have mass-weighted stellar ages

102 of 5Gyr or more, and are either passive and gas depleted or have outflows and thus are in the process of losing their gas.

I also found that galaxies with AGN-driven outflows have diverse star formation histories, but have consistently older stellar populations than those with star formation- driven outflows. Of the galaxies with outflows, two host AGN, yet have symmetrical line profiles and broad component flux ratios falling in the composite region of the BPTdiagram.

These galaxies also happen to have very young (< 3 Gyr) populations and are growing a larger fraction of their stellar masses at present day than any other AGN in the sample.

This lends support to the notion that the outflows in these galaxies are driven bystar formation.

Isolated counter-rotating galaxies have star formation histories that differ from those with neighbors. The two counter-rotating galaxies residing in isolation have quickly rising cumulative mass fractions, with little to no present day star formation. On the other hand, the three counter-rotating galaxies that reside in rather busy environments show slow growth between z = 1 − 0.2 and a recent burst of star formation, presumably associated with the newly accreted gas. I suspect that galaxies in crowded environments obtain counter-rotating gas through minor mergers with gas-rich, star forming dwarfs, while isolated galaxies accrete small amounts non-star forming gas.

There is still much to learn from this collection of Keck-LRIS data. Gas phase metallicities can provide insight on the present day metal enrichment of the ISM and the

103 transport of metals between these dwarfs and their surroundings. Rotation curves which decompose young and old stellar populations could reveal counter-rotating stellar disks, providing insight into the merger histories of these objects.

A significant fraction of the AGN in our sample contain outflows, so a systematic search for AGN-driven outflows in a much larger parent sample could reveal the extent to which AGN-driven outflows are present in this mass range. Follow-up observations to obtain multiphase gas kinematic measurements, gas mass measurements, and wider IFU coverage of the ionized gas kinematics would deepen our understanding of the processes at play within these dwarfs. Furthermore, it is possible that the disturbed gas is triggering the AGN, rather than the AGN disturbing the gas. It would be interesting to explore this reverse scenario and ask what activated the AGN in the first place. Follow-up HI observations would be useful for investigating this question.

Detailed, spatially resolved kinematic measurements such as the ones presented in this work provide vital observational constraints needed to extend realistic feedback models into the low-mass regime. Considering the expected prevalence of AGN in dwarf galaxies, their strong effect on dwarf galaxy gas kinematics, and their apparent association with star formation suppression, future generations of simulations should account for this important source of feedback.

104 Appendix A

A.1 Black Hole Masses

Line broadening from the Broad Line Region (BLR) associated with the AGN is sometimes observed in Balmer emission lines (see Figure 2.4) and can be used to measure

BH masses. Due to the small spatial extent of the BLR and the low transition probability of forbidden lines, BLR emission does not contribute to the line profiles of [O iii]λ5007, which we use to trace the kinematics of fast-moving winds throughout the galaxy. In this section, we explore the presence of an additional BLR component in Hα (purple line in the third panel of Fig. 2.4), associated with the BH itself, not to be confused with the broadened components associated with galaxy-scale outflows (orange lines in Fig. 2.4).

We detect a previously unreported broad Hα line in J084234.51+031930.7 and

5 measure its virial mass to be MBH = 6.92 × 10 M⊙, using RGG13 Equation 5, which relies on the RBLR − L relation of [24].

( ) ( ) LHα FWHMHα log(MBH /M⊙) = log(ϵ) + 6.57 + 0.47 log + 2.06 log (A.1) 1042 erg s−1 103 km s−1

105 Black hole masses for 5 more AGN in this sample are reported in the literature using this approach, yet once outflow components are included in the[N ii], Hα narrow line model, we find no additional BLR Hα components in the other AGN discussed here. We therefore caution that line broadening due to outflowing gas could masquerade as aBLR broad line, so it is necessary to check for outflow contributions in forbidden lines such as

[O iii] and model them whenever possible when deriving black hole masses from heavily

blended complexes such as Hα + [N ii].

A.2 Spatial Properties of Outflows

Appendix Figure .1 shows the spatial properties of the outflows of the remaining

12 galaxies, as in Fig. 2.7.

A.3 Inclination Correction

ppxf returns line of sight velocities. In order to translate the line of sight velocities measured in ppxf into rotational velocities, the inclination angle must be accounted for.

The inclination angle θinc of a galaxy is defined as the angle between the line of sight and the normal to the disc. A perfectly round disc, inclined by θinc is projected as an ellipse in

an image, with semimajor axis a and semiminor axis b. Assuming an infinitely thin disc,

−1 θinc = cos (b/a). More realistically, we can introduce a thickness parameter q = c/a, which describes a circular disc of radius a and thickness c, as illustrated in Figure A.2. The

106 projection of this shape when imaged is still approximately elliptical, and the inclination angle can more accurately be estimated using

(b/a)2 − q2 cos−1(θ ) = (A.2) inc 1 − q2

The ellipticity (b/a) was obtained by a fit to the SDSS r−band image using the

Python package photutils [42]. In the absence of any constraint on galaxy morphology, we

used a range of q = 0.1 − 0.2 [125].

It is straightforward to translate line of sight velocity to circular velocity using the inclination angle:

vlos vrot = (A.3) sin(θinc)

The range of inclination angles then translates to a range of possible vrot values.

The vlos measurements are corrected using the mean value for θinc. The minimum and maximum values for θinc are used to estimate the error introduced to the vrot measurements

by the uncertainty in inclination.

We forego inclination correction for two cases (J081145.29+232825.7 and J084234.51

+031930.7) where the inclination angle is less than 20 degrees. These galaxies are viewed

face-on, and show no distinct rotation. Their gas kinematics imply a stratified narrow line

region with a non-rotational, possibly spherical outflow (see Section 3.4.2). If this isthe

case, line of sight velocities are more physically meaningful than rotational velocities.

107 A.4 All rotation curves

In this appendix, we present all 45 rotation curves included in this analysis. Each curve was measured following the process described in Section 3.3. Spatially resolved spectra were extracted as described in Section 3.3.1, and kinematic measurements were obtained by spectral fits performed using ppxf (Section 3.3.3). Each rotation curve consists of three components: stellar velocity (gray stars), gas velocity from Balmer emission lines (orange circles), and gas velocity from forbidden emission lines. Whenever possible, the forbidden emission line velocities are measured from [O iii] (teal circles). [O ii] (purple circles) were used for spectra obtained using the 5000Å dichroic. When gas emission was faint (Hβ equivalent width less than 0.5Å or [O iii] equivalent width less than 2.0 Å), we use longer wavelengths to perform kinematic measurements. In this case, Balmer gas velocities were measured from Hα and [S ii]] (blue circles) were used to measure the forbidden emission line component.

Gray shaded regions denote the rotation curve predicted by assuming an NFW dark matter profile, with halo mass obtained using abundance matching, with theMPA stellar mass as input (see Section 3.4). The spatial axis is normalized by the SDSS r-band petrosian radius, r50.

The velocity measurements and associated errors are corrected for disc inclination as described in Appendix A.3. The angle relative to the normal of the disc and the stellar mass, as listed in the MPA-JHU catalogue, are shown in the bottom left of each curve plot.

∆off is shown on the bottom right.

108 Asymmetric drift, or the difference between the local circular speed and the mean rotation of the galaxy, acts to reduce the observed rotational velocity due to the presence of randomly oriented and non-circular orbits. In the absence of gas surface density measurements, we do not correct for asymmetric drift.

109 J0100-01 3000 J1442+20 1000 J0811+23 ) ) )

1 800 1 2500 1 900 − − − s 700 s 2000 s 800 m 600 m m k k k

( ( 1500 ( 700

0 500 0 0 8 400 8 1000 8 600 W W W 1.0 0.5 0.0 0.5 1.0 ) 150 ) ) 30 1 1 100 1 − − − 60 s 100 s s

m m 0 m 90

k 50 k k ( ( ( 120

0 0 100 0 v 0 v v 150 101 100 100 1.0 0.5 0.0 0.5 1.0 0

n 10 n n

F F -1 F -1

/ / 10 / 10 b -1 b b F 10 F F

10-2 10-2 10-2 1.0 0.5 0.0 0.5 1.0 1.5 1.0 0.5 0.0 0.5 1.0 1.5 0.6 0.4 0.2 0.0 0.2 0.4 0.6 r (kpc) r (kpc) r (kpc)

J0840+18 J0842+03 J0954+47 ) )

1 650 1

− 1700 − 1800 s s 0 8 m 1400 600 m 1500 k k W ( ( 1200 0 0

8 550 8 1100 900 W W

150 0.6 0.4 0.2 0.0 0.2 0.4 0.6 20 2 1 0 1 2 ) ) ) 0 1 100 1 1 − − 40 − 20 s 50 s 60 s

m 0 m m 40

k 50 k 80 k ( ( ( 60

0 100 0 100 0 v 150 v 120 v 80 100 101 101 0.6 0.4 0.2 0.0 0.2 0.4 0.6 2 1 0 1 2 n n n

F -1 F F 0

/ 10 / / 10 b b b F F F

10-2 100 10-1 0.6 0.4 0.2 0.0 0.2 0.4 0.6 0.6 0.4 0.2 0.0 0.2 0.4 0.6 2 1 0 1 2 r (kpc) r (kpc) r (kpc)

J1005+12 J1009+26 J1014+19 2100 2300 2100 ) ) 1 1

1800 − 2000 − 1800 s s 0 8

1500 m 1700 m 1500 k k W 1200 ( 1400 ( 1200 0 0 900 8 1100 8 900 W W

) 50 ) ) 1 1 50 1 − − − 0 s 100 s s

m m 50 m 100 k 150 k k ( ( (

0 0 150 0 200 v 200 v v 101 101 101

0 0

n n 10 n 10

F 0 F F

/ 10 / / b b -1 b -1 F F 10 F 10

10-1 10-2 10-2 0.6 0.4 0.2 0.0 0.2 0.4 0.6 1.5 1.0 0.5 0.0 0.5 1.0 1.5 2 1 0 1 2 r (kpc) r (kpc) r (kpc)

110 J1307+52 J1717+33 NGC_1569 2600 2700 ) ) ) 3500 1 1 1

− 2300 − 2400 −

s s s 3000

m 2000 m 2100 m 2500 k k k ( ( 1800 ( 0 0 0 2000 8 1700 8 1500 8

W W W 1500 400 ) 150 ) 100 ) 1 1 1

− 100 − − 200 s s 0 s

m 50 m m 0

k k 100 k ( 0 ( ( 200 0 0 0

v v 200 v 50 400 101 100 0 0 10

n 10 n n

F F -1 F

/ / 10 / b -1 b b -1 F 10 F F 10

10-2 10-2 10-2 3 2 1 0 1 2 3 3 2 1 0 1 2 3 0.3 0.2 0.1 0.0 0.1 0.2 0.3 r (kpc) r (kpc) r (kpc)

Figure A.1: Spatially resolved properties of outflows are presented for the remaining 12 galaxies, as in Fig. 2.7. Consistent with the scheme used throughout this paper, AGN- driven outflows are plotted with pink circles, star forming with cyan triangles, andAGN with SF outflows with black diamonds.

b a

θinc

Figure A.2: A diagram to illustrate how a disc with thickness c appears as an ellipse when viewed from the inclination angle θinc. The inclination angle can be estimated by measuring the ellipse semimajor and minor axes a, b and assuming the disc thickness c.

111 J0021+00 J0802+10 J0851+39 J1401+54 100 ) s /

m 0 k (

v 100 θ = 52.44 θ = 32.14 θ = 50.41 θ = 69.54 log(M ) = 9.15 ∆ = 0.64 log(M ) = 9.60 ∆ = 0.50 log(M ) = 9.28 ∆ = 0.42 log(M ) = 9.57 ∆ = 0.24 ∗ ∗ ∗ ∗ J1405+115 0 5 J1407+505 0 5 J1546+035 0 5 5 0 5 100 stellar r/r50 r/r50 r/r50 r/r50

) Hα or Hβ s /

m 0 [OII] k ( [OIII] v 100 θ = 74.10 θ = 69.24 θ = 85.97 [SII] log(M ) = 9.23 ∆ = 0.48 log(M ) = 8.72 ∆ = 0.30 log(M ) = 9.49 ∆ = 0.19 ∗ ∗ ∗ 5 0 5 5 0 5 5 0 5 5 0 5 r/r50 r/r50 r/r50 r/r50

Figure A.3: Twenty of the 45 galaxies with rotation curves have gas that rotates with the stellar component. The shaded regions denote velocity curves following NFW profiles, assuming concentration parameters between c = 8, 15. Galaxies hosting AGN are shown in the top panel and star forming galaxies are in the bottom.

112 J0156-00 J0911+61 J1014+19 J1623+39 100 ) s /

m 0 k (

v 100 θ = 70.21 θ = 85.40 θ = 45.23 θ = 68.86 log(M ) = 9.39 ∆ = 0.98 log(M ) = 8.95 ∆ = 9.16 log(M ) = 8.56 ∆ = 3.03 log(M ) = 9.22 ∆ = 1.36 ∗ ∗ ∗ ∗ J1717+335 0 5 J1722+285 0 5 5 0 5 5 0 5 100 stellar r/r50 r/r50 r/r50 r/r50

) Hα or Hβ s /

m 0 [OII] k ( [OIII] v 100 θ = 60.70 θ = 76.84 [SII] log(M ) = 9.85 ∆ = 1.54 log(M ) = 9.25 ∆ = 0.76 ∗ ∗ 5 0 5 5 0 5 5 0 5 5 0 5 r/r50 r/r50 r/r50 r/r50

Figure A.4: Twenty-five of the 45 galaxies with rotation curves have disturbed gas.See Section 3.4.2 for a discussion on how we classify galaxies as disturbed. Galaxies hosting AGN are shown in the top group and star forming galaxies are in the bottom.

113 J0100-01 J0811+23 J0842+03 J0906+56 100 ) s /

m 0 k (

v 100 θ = 43.88 θ = 15.70 θ = 18.24 θ = 22.53 log(M ) = 9.44 ∆ = 0.68 log(M ) = 9.06 ∆ = 8.33 log(M ) = 9.33 ∆ = 2.43 log(M ) = 9.37 ∆ = 0.61 ∗ ∗ ∗ ∗ J0948+095 0 5 J1002+595 0 5 J1442+205 0 5 5 0 5 100 stellar r/r50 r/r50 r/r50 r/r50

) Hα or Hβ s /

m 0 [OII] k ( [OIII] v 100 θ = 47.19 θ = 43.82 θ = 32.27 [SII] log(M ) = 8.73 ∆ = 3.53 log(M ) = 9.60 ∆ = 0.98 log(M ) = 8.89 ∆ = 10.20 ∗ ∗ ∗ 5 0 5 5 0 5 5 0 5 5 0 5 r/r50 r/r50 r/r50 r/r50

Figure A.5: Eight of the 45 galaxies with rotation curves show stratification in their emission lines. See Section 3.4.2 for a discussion on how we identify line stratification. Line of sight velocity gradients are shown for J0811+23 and J0842+03, as they are considered face-on based on their small inclination angles (θ < 20◦) and thus are not corrected for inclination (as described in Appendix A.4). Rotational velocity curves (corrected for disc inclination) are shown for all other galaxies in this figure.

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